The genomic mechanism responsible for malignant transformation remains an open question for glioma researchers, where differing conclusions have been drawn based on diverse study conditions. Therefore, it is essential to secure direct evidence using longitudinal samples from the same patient. Moreover, malignant transformation of IDH1-mutated gliomas is of potential interest, as its genomic mechanism under influence of oncometabolite remains unclear, and even higher rate of malignant transformation was reported in IDH1-mutated low grade gliomas than in wild-type IDH1 tumors. We have analyzed genomic data using next-generation sequencing technology for longitudinal samples from 3 patients with IDH1-mutated gliomas whose disease had progressed from a low grade to a high grade phenotype. Comprehensive analysis included chromosomal aberrations as well as whole exome and transcriptome sequencing, and the candidate driver genes for malignant transformation were validated with public database. Integrated analysis of genomic dynamics in clonal evolution during the malignant transformation revealed alterations in the machinery regulating gene expression, including the spliceosome complex (U2AF2), transcription factors (TCF12), and chromatin remodelers (ARID1A). Moreover, consequential expression changes implied the activation of genes associated with the restoration of the stemness of cancer cells. The alterations in genetic regulatory mechanisms may be the key factor for the major phenotypic changes in IDH1 mutated gliomas. Despite being limited to a small number of cases, this analysis provides a direct example of the genomic changes responsible for malignant transformation in gliomas.

Although adolescent and young adult (AYA) cancers are characterized by biological features and clinical outcomes distinct from those of other age groups, the molecular profile of AYA cancers has not been well defined. In this study, we analyzed cancer genomes from rare types of metastatic AYA cancers to identify driving and/or druggable genetic alterations.

Fluorescence-guided surgery using 5-aminolevulinic acid (5-ALA) has become the main treatment modality in malignant gliomas. However unlike glioblastomas, there are inconsistent result about fluorescence status in WHO grade III gliomas. Here, we show that mutational status of IDH1 is linked to 5-ALA fluorescence. Using genetically engineered malignant glioma cells harboring wild type (U87MG-IDH1WT) or mutant (U87MG-IDH1R132H) IDH1, we demonstrated a lag in 5-ALA metabolism and accumulation of protoporphyrin IX (PpIX) in U87MG-IDH1R132Hcells. Next, we used liquid chromatography-mass spectrometry (LC-MS) to screen for tricarboxylic acid (TCA) cycle-related metabolite changes caused by 5-ALA exposure. We observed low baseline levels of NADPH, an essential cofactor for the rate-limiting step of heme degradation, in U87MG-IDH1R132H cells. High levels of NADPH are required to metabolize excessive 5-ALA, giving a plausible reason for the temporarily enhanced 5-ALA fluorescence in mutant IDH1 cells. This hypothesis was supported by the results of metabolic screening in human malignant glioma samples. In conclusion, we have discovered a relationship between enhanced 5-ALA fluorescence and IDH1 mutations in WHO grade III gliomas. Low levels of NADPH in tumors with mutated IDH1 is responsible for the enhanced fluorescence.

Fluorescence-guided surgery using 5-aminolevulinic acid (5-ALA) is now a widely-used modality for glioblastoma (GBM) treatment. However, intratumoral heterogeneity of fluorescence intensity may reflect different onco-metabolic programs. Here, we investigated the metabolic mechanism underlying the heterogeneity of 5-ALA fluorescence in GBM. Using an in-house developed fluorescence quantification system for tumor tissues, we collected 3 types of GBM tissues on the basis of their fluorescence intensity, which was characterized as strong, weak, and none. Expression profiling by RNA-sequencing revealed 77 genes with a proportional relationship and 509 genes with an inverse relationship between gene expression and fluorescence intensity. Functional analysis and in vitro experiments confirmed glutaminase 2 (GLS2) as a key gene associated with the fluorescence heterogeneity. Subsequent metabolite profiling discovered that insufficient NADPH due to GLS2 underexpression was responsible for the delayed metabolism of 5-ALA and accumulation of protoporphyrin IX (PpIX) in the high fluorescence area. The expression level of GLS2 and related NADPH production capacity is associated with the regional heterogeneity of 5-ALA fluorescence in GBM.

Intratumoral heterogeneity has been suggested to be an important resistance mechanism leading to treatment failure. We hypothesized that radiologic images could be an alternative method for identification of tumor heterogeneity. We tested heterogeneity textural parameters on pretreatment FDG-PET/CT in order to assess the predictive value of target therapy. Recurred or metastatic non-small cell lung cancer (NSCLC) subjects with an activating EGFR mutation treated with either gefitinib or erlotinib were reviewed. An exploratory data set (n = 161) and a validation data set (n = 21) were evaluated, and eight parameters were selected for survival analysis. The optimal cutoff value was determined by the recursive partitioning method, and the predictive value was calculated using Harrell's C-index. Univariate analysis revealed that all eight parameters showed an increased hazard ratio (HR) for progression-free survival (PFS). The highest HR was 6.41 (P<0.01) with co-occurrence (Co) entropy. Increased risk remained present after adjusting for initial stage, performance status (PS), and metabolic volume (MV) (aHR: 4.86, P<0.01). Textural parameters were found to have an incremental predictive value of early EGFR tyrosine kinase inhibitor (TKI) failure compared to that of the base model of the stage and PS (C-index 0.596 vs. 0.662, P = 0.02, by Co entropy). Heterogeneity textural parameters acquired from pretreatment FDG-PET/CT are highly predictive factors for PFS of EGFR TKI in EGFR-mutated NSCLC patients. These parameters are easily applicable to the identification of a subpopulation at increased risk of early EGFR TKI failure. Correlation to genomic alteration should be determined in future studies.

Thymic adenocarcinoma is an extremely rare subtype of thymic epithelial tumors. Due to its rarity, there is currently no sequencing approach for thymic adenocarcinoma.

The purpose of this study was to evaluate potential prognostic factors in patients with adenoid cystic carcinoma (ACC).

Treatment of human lung squamous cell carcinoma (LUSC) using current targeted therapies is limited because of their diverse somatic mutations without any specific dominant driver mutations. These mutational diversities preventing the use of common targeted therapies or the combination of available therapeutic modalities would require a preclinical animal model of this tumor to acquire improved clinical responses. Patient-derived xenograft (PDX) models have been recognized as a potentially useful preclinical model for personalized precision medicine. However, whether the use of LUSC PDX models would be appropriate enough for clinical application is still controversial.

Although anti-programmed death-1 (PD-1) treatment has shown remarkable anti-tumor efficacy, immune-related adverse events (irAEs) develop with heterogeneous clinical manifestations. However, the immunological understanding of irAEs is currently limited. In the present study, we analyzed peripheral blood T cells obtained from cancer patients who received anti-PD-1 treatment to determine the immunological characteristics of irAEs. This study included 31 patients with refractory thymic epithelial tumor (TET) who were enrolled in a phase II trial of pembrolizumab (NCT02607631) and 60 patients with metastatic non-small cell lung cancer (NSCLC) who received pembrolizumab or nivolumab. T-cell profiling was performed by multicolor flow cytometry using peripheral blood obtained before treatment and 7 days after the first dose of anti-PD-1 antibodies. irAEs developed in 21 TET patients and 24 NSCLC patients. Severe (≥ grade 3) irAEs occurred in 7 TET patients (22.6%) and 6 NSCLC patients (10.0%). Patients with severe irAEs exhibited a significantly lower fold increase in the frequency of effector regulatory T (eTreg) cells after anti-PD-1 treatment, a higher ratio of T helper-17 (Th17) and T helper-1 cells at baseline, and a higher percentage of Ki-67+ cells among PD-1+CD8+ T cells posttreatment. In clustering analysis using the T-cell parameters, patients with irAEs were grouped into four distinct subtypes: Th17-related, TNF-related, CD8-related Treg-compensated, and CD8-related Treg-uncompensated. The T-cell parameters showed a predictive value for the development of each subtype of severe irAEs. In conclusion, severe irAEs after anti-PD-1 treatment were clustered into four immunological subtypes, and potential biomarkers for early prediction of severe irAEs were proposed.

We aimed to develop a deep learning (DL) model for predicting high-grade patterns in lung adenocarcinomas (ADC) and to assess the prognostic performance of model in advanced lung cancer patients who underwent neoadjuvant or definitive concurrent chemoradiation therapy (CCRT). We included 275 patients with 290 early lung ADCs from an ongoing prospective clinical trial in the training dataset, which we split into internal-training and internal-validation datasets. We constructed a diagnostic DL model of high-grade patterns of lung ADC considering both morphologic view of the tumor and context view of the area surrounding the tumor (MC3DN; morphologic-view context-view 3D network). Validation was performed on an independent dataset of 417 patients with advanced non-small cell lung cancer who underwent neoadjuvant or definitive CCRT. The area under the curve value of the DL model was 0.8 for the prediction of high-grade histologic patterns such as micropapillary and solid patterns (MPSol). When our model was applied to the validation set, a high probability of MPSol was associated with worse overall survival (probability of MPSol >0.5 vs. <0.5; 5-year OS rate 56.1% vs. 70.7%), indicating that our model could predict the clinical outcomes of advanced lung cancer patients. The subgroup with a high probability of MPSol estimated by the DL model showed a 1.76-fold higher risk of death (HR 1.76, 95% CI 1.16-2.68). Our DL model can be useful in estimating high-grade histologic patterns in lung ADCs and predicting clinical outcomes of patients with advanced lung cancer who underwent neoadjuvant or definitive CCRT.

Pancreaticobiliary tract cancer has a poor prognosis with unmet needs in a new target treatment. Some studies have reported that an enhancement of T-cell immunity is associated with a good prognosis. The aim of this study is to investigate the immunoprofile as a prognostic marker of pancreaticobiliary tract cancers. Unresectable pancreatic ductal adenocarcinoma (PDAC, n = 80) and biliary tract cancer (BTC, n = 74) diagnosed between January 2012 and December 2018 in Samsung Medical Center were analyzed. Expression levels of CD8, FOXP3, PD-1, PD-L1, and CXCL13 in PDAC and BTC tissue samples were examined with immunohistochemical staining, which was evaluated with various clinical factors. In PDAC, higher degree of PD-L1 expression was significantly associated with shorter overall survival (OS) (p = 0.0095). On the other hand, higher infiltrations of PD-1+ immune cells (p = 0.0002) and CD8+ T cells (p = 0.0067) were associated with longer OS. In BTC, higher FOXP3+ (p = 0.0343) and CD8+ (p = 0.0028) cell infiltrations were associated with better survival. Low infiltration of CD8+ (p = 0.0148), FOXP3+ (p = 0.0208), PD-1+ (p = 0.0318) cells in PDAC, and FOXP3+ cells (p = 0.005) in BTC were considerably related to metastasis. In a combined evaluation of clinical factors and immunoprofiles, univariate analysis revealed that operation after chemotherapy (p < 0.0001), mass size (p = 0.0004), metastasis (p = 0.006), PD-L1 (p < 0.0001), PD-1 (p = 0.003) and CD8 (p = 0.0063) was significantly associated with OS in PDAC, and CD8 (p = 0.007) was statistically related to OS in BTC. In multivariate analysis, prognostic factors were operation after chemotherapy (p = 0.021) in PDAC and CD8 (p = 0.037) in BTC. Therefore, immunoprofile analysis of cells expressing CD8, FOXP3, PD-1, and PD-L1 might have prognostic values in patients with pancreaticobiliary tract cancers.

Checkpoint inhibitors (CPIs) augment adaptive immunity. Systematic pan-tumor analyses may reveal the relative importance of tumor-cell-intrinsic and microenvironmental features underpinning CPI sensitization. Here, we collated whole-exome and transcriptomic data for >1,000 CPI-treated patients across seven tumor types, utilizing standardized bioinformatics workflows and clinical outcome criteria to validate multivariable predictors of CPI sensitization. Clonal tumor mutation burden (TMB) was the strongest predictor of CPI response, followed by total TMB and CXCL9 expression. Subclonal TMB, somatic copy alteration burden, and histocompatibility leukocyte antigen (HLA) evolutionary divergence failed to attain pan-cancer significance. Dinucleotide variants were identified as a source of immunogenic epitopes associated with radical amino acid substitutions and enhanced peptide hydrophobicity/immunogenicity. Copy-number analysis revealed two additional determinants of CPI outcome supported by prior functional evidence: 9q34 (TRAF2) loss associated with response and CCND1 amplification associated with resistance. Finally, single-cell RNA sequencing (RNA-seq) of clonal neoantigen-reactive CD8 tumor-infiltrating lymphocytes (TILs), combined with bulk RNA-seq analysis of CPI-responding tumors, identified CCR5 and CXCL13 as T-cell-intrinsic markers of CPI sensitivity.

The immunogenomic changes triggered by concurrent chemoradiation therapy (CCRT), a standard neoadjuvant treatment for locally advanced esophageal squamous cell carcinoma (ESCC), are unknown. We aimed to analyze the early immunogenomic changes in ESCC induced by CCRT and to correlate them with clinical outcomes.

This study investigated the associations between image features extracted from tumor 18F-fluorodeoxyglucose (FDG) uptake and genetic alterations in patients with lung cancer. A total of 137 patients (age, 62.7 ± 10.2 years) who underwent FDG positron emission tomography/computed tomography (PET/CT) and targeted deep sequencing analysis for a tumor lesion, comprising 61 adenocarcinoma (ADC), 31 squamous cell carcinoma (SQCC), and 45 small cell lung cancer (SCLC) patients, were enrolled in this study. From the tumor lesions, 86 image features were extracted, and 381 genes were assessed. PET features were associated with genetic mutations: 41 genes with 24 features in ADC; 35 genes with 22 features in SQCC; and 43 genes with 25 features in SCLC (FDR < 0.05). Clusters based on PET features showed an association with alterations in oncogenic signaling pathways: Cell cycle and WNT signaling pathways in ADC (p = 0.023, p = 0.035, respectively); Cell cycle, p53, and WNT in SQCC (p = 0.045, 0.009, and 0.029, respectively); and TGFβ in SCLC (p = 0.030). In addition, SUVpeak and SUVmax were associated with a mutation of the TGFβ signaling pathway in ADC (FDR = 0.001, < 0.001). In this study, PET image features had significant associations with alterations in genes and oncogenic signaling pathways in patients with lung cancer.

Patritumab deruxtecan, or HER3-DXd, is an antibody-drug conjugate consisting of a fully human monoclonal antibody to human epidermal growth factor receptor 3 (HER3) attached to a topoisomerase I inhibitor payload via a stable tetrapeptide-based cleavable linker. We assessed the efficacy and safety of HER3-DXd in patients with epidermal growth factor receptor (EGFR)-mutated non-small-cell lung cancer (NSCLC).

Genomic hypomethylation has recently been identified as a determinant of therapeutic responses to immune checkpoint blockade (ICB). However, it remains unclear whether this approach can be applied to cell-free DNA (cfDNA) and whether it can address the issue of low tumor purity encountered in tissue-based methylation profiling. In this study, we developed an assay named iMethyl, designed to estimate the genomic hypomethylation status from cfDNA. This was achieved through deep targeted sequencing of young LINE-1 elements with > 400,000 reads per sample. iMethyl was applied to a total of 653 ICB samples encompassing lung cancer (cfDNA n = 167; tissue n = 137; cfDNA early during treatment n = 40), breast cancer (cfDNA n = 91; tissue n = 50; PBMC n = 50; cfDNA at progression n = 44), and ovarian cancer (tissue n = 74). iMethyl-liquid predicted ICB responses accurately regardless of the tumor purity of tissue samples. iMethyl-liquid was also able to monitor therapeutic responses early during treatment (3 or 6 weeks after initiation of ICB) and detect progressive hypomethylation accompanying tumor progression. iMethyl-tissue had better predictive power than tumor mutation burden and PD-L1 expression. In conclusion, our iMethyl-liquid method allows for reliable noninvasive prediction, early evaluation, and monitoring of clinical responses to ICB therapy.

The aim of this study was to develop a pragmatic nomogram for prediction of progressionfree survival (PFS) for the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) in EGFR mutant non-small cell lung cancer (NSCLC).

Atypical teratoid/rhabdoid tumors (AT/RTs) are highly malignant brain tumors with inactivation of the SMARCB1 gene, which play a critical role in genomic transcriptional control. In this study, we analyzed the genomic and transcriptomic profiles of human AT/RTs to discover new druggable targets.

Anemia is the most common and serious cancer-related complication. This study aimed to evaluate the efficacy of administration of ferric carboxymaltose without erythropoiesis-stimulating agents for treating anemia in cancer patients. Moreover, we identified the biomarkers of hemoglobin response to predict the need for iron therapy.

AZD9291 (osimertinib) is approved for standard care in patients with EGFR T790M-positive non-small cell lung cancer (NSCLC) after prior EGFR TKI progression. Furthermore, AZD9291 is now being evaluated as a first-line treatment for NSCLC patients with activation EGFR mutations. Based on previous experiments, resistance to AZD9291 as a first-line treatment may also emerge. Thus, identification and understanding of resistance mechanisms to AZD9291 as a first-line treatment can help direct development of future therapies. AZD9291-resistant cells (PC9/AZDR) were established using EGFR inhibitor-naïve PC9 cells. Resistance mechanisms were analyzed using next-generation sequencing (NGS) and a proteome profiler array. Resistance to AZD9291 developed through aberrant activation of ERK signaling by an EGFR-independent mechanism. The combination of a MEK inhibitor with AZD9291 restored the sensitivity of PC9/AZDR cells in vitro and in vivo. PC9/AZDR cells also showed increased MET expression and an HRAS G13R mutation. In addition, maspin expression was higher after AZD9291 treatment in PC9/AZDR cells. Sustained ERK activation confers resistance to AZD9291 as a first-line therapy. Thus, co-targeting EGFR and MEK may be an effective strategy to overcome resistance to AZD9291.