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Clonal hematopoiesis of indeterminate potential (CHIP) allows estimation of clonal dynamics and documentation of somatic mutations in the hematopoietic system. Recent studies utilizing large cohorts of the general population and patients have revealed significant associations of CHIP burden with age and disease status, including in cancer and chronic diseases. An increasing number of cancer patients are treated with immune checkpoint inhibitors (ICIs), but the association of ICI response in non-small cell lung cancer (NSCLC) patients with CHIP burden remains to be determined. We collected blood samples from 100 metastatic NSCLC patients before and after ICI for high-depth sequencing of the CHIP panel and 63 samples for blood single-cell RNA sequencing. Whole exome sequencing was performed in an independent replication cohort of 180 patients. The impact of CHIP status on the immunotherapy response was not significant. However, metastatic lung cancer patients showed higher CHIP prevalence (44/100 for patients vs. 5/42 for controls; p = 0.01). In addition, lung squamous cell carcinoma (LUSC) patients showed increased burden of larger clones compared to lung adenocarcinoma (LUAD) patients (8/43 for LUSC vs. 2/50 for LUAD; p = 0.04). Furthermore, single-cell RNA-seq analysis of the matched patients showed significant enrichment of inflammatory pathways mediated by NF-κB in myeloid clusters of the severe CHIP group. Our findings suggest minimal involvement of CHIP mutation and clonal dynamics during immunotherapy but a possible role of CHIP as an indicator of immunologic response in NSCLC patients.

Abstract Neoantigens are ideal targets for cancer immunotherapy because they are expressed de novo in tumor tissue but not in healthy tissue and are therefore recognized as foreign by the immune system. Advances in next-generation sequencing and bioinformatics technologies have enabled the quick identification and prediction of tumor-specific neoantigens; however, only a small fraction of predicted neoantigens are immunogenic. To improve the predictability of immunogenic neoantigens, we developed the in silico neoantigen prediction workflows VACINUSpMHC and VACINUSTCR: VACINUSpMHC incorporates physical binding between peptides and MHCs (pMHCs), and VACINUSTCR integrates T cell reactivity to the pMHC complex through deep learning-based pairing with T cell receptors (TCRs) of putative tumor-reactive CD8 tumor-infiltrating lymphocytes (TILs). We then validated our neoantigen prediction workflows both in vitro and in vivo in patients with hepatocellular carcinoma (HCC) and in a B16F10 mouse melanoma model. The predictive abilities of VACINUSpMHC and VACINUSTCR were confirmed in a validation cohort of 8 patients with HCC. Of a total of 118 neoantigen candidates predicted by VACINUSpMHC, 48 peptides were ultimately selected using VACINUSTCR. In vitro validation revealed that among the 48 predicted neoantigen candidates, 13 peptides were immunogenic. Assessment of the antitumor efficacy of the candidate neoepitopes using a VACINUSTCR in vivo mouse model suggested that vaccination with the predicted neoepitopes induced neoantigen-specific T cell responses and enabled the trafficking of neoantigen-specific CD8 + T cell clones into the tumor tissue, leading to tumor suppression. This study showed that the prediction of immunogenic neoantigens can be improved by integrating a tumor-reactive TIL TCR-pMHC ternary complex.

Objective Recent studies have reported that gout is associated with a risk of cardiovascular disease (CVD) later in life. However, the predictive value of genetic predisposition to gout combined with lifestyle habits for CVD risk remains unclear. This study aimed to examine the association between genetic predisposition to gout and lifestyle habits and the risk of developing CVD in two diverse prospective cohorts from different ancestries.Methods A total of 224 689 participants of European descent from the UK Biobank and 50 364 participants of East Asian descent from the Korean Genome and Epidemiology Study were included. The genetic risk for gout was assessed using a polygenic risk score (PRS) derived from a meta-genome-wide association study (n=444 533). The incident CVD risk was evaluated according to genetic risk, lifestyle and metabolic syndrome (MetS).Results Individuals at high genetic risk for gout had a higher risk of incident CVD than those with low genetic risk across ancestry. Notably, a reduction in CVD risk by up to 62% (HR 0.38; 95% CI 0.31 to 0.46; p

Summary: Background: Interstitial lung disease (ILD) poses a serious threat in patients with rheumatoid arthritis (RA). However, the impact of cornerstone drugs, including methotrexate (MTX) and TNF inhibitor, on RA-associated ILD (RA-ILD) remains controversial. Methods: Using an SKG mouse model and single-cell transcriptomics, we investigated the effects of MTX and TNF blockade on ILD. Findings: Our study revealed that MTX exacerbates pulmonary inflammation by promoting immune cell infiltration, Th17 activation, and fibrosis. In contrast, TNF inhibitor ameliorates these features and inhibits ILD progression. Analysis of data from a human RA-ILD cohort revealed that patients with ILD progression had persistently higher systemic inflammation than those without progression, particularly among the subgroup undergoing MTX treatment. Interpretation: These findings highlight the need for personalized therapeutic approaches in RA-ILD, given the divergent outcomes of MTX and TNF inhibitor. Funding: This work was funded by GENINUS Inc., and the National Research Foundation of Korea, and Seoul National University Hospital.

Abstract Background Numerous observational studies have highlighted associations of genetic predisposition of head and neck squamous cell carcinoma (HNSCC) with diverse risk factors, but these findings are constrained by design limitations of observational studies. In this study, we utilized a phenome-wide association study (PheWAS) approach, incorporating a polygenic risk score (PRS) derived from a wide array of genomic variants, to systematically investigate phenotypes associated with genetic predisposition to HNSCC. Furthermore, we validated our findings across heterogeneous cohorts, enhancing the robustness and generalizability of our results. Methods We derived PRSs for HNSCC and its subgroups, oropharyngeal cancer and oral cancer, using large-scale genome-wide association study summary statistics from the Genetic Associations and Mechanisms in Oncology Network. We conducted a comprehensive investigation, leveraging genotyping data and electronic health records from 308,492 individuals in the UK Biobank and 38,401 individuals in the Penn Medicine Biobank (PMBB), and subsequently performed PheWAS to elucidate the associations between PRS and a wide spectrum of phenotypes. Results We revealed the HNSCC PRS showed significant association with phenotypes related to tobacco use disorder (OR, 1.06; 95% CI, 1.05–1.08; P = 3.50 × 10−15), alcoholism (OR, 1.06; 95% CI, 1.04–1.09; P = 6.14 × 10-9), alcohol-related disorders (OR, 1.08; 95% CI, 1.05–1.11; P = 1.09 × 10−8), emphysema (OR, 1.11; 95% CI, 1.06–1.16; P = 5.48 × 10−6), chronic airway obstruction (OR, 1.05; 95% CI, 1.03–1.07; P = 2.64 × 10−5), and cancer of bronchus (OR, 1.08; 95% CI, 1.04–1.13; P = 4.68 × 10−5). These findings were replicated in the PMBB cohort, and sensitivity analyses, including the exclusion of HNSCC cases and the major histocompatibility complex locus, confirmed the robustness of these associations. Additionally, we identified significant associations between HNSCC PRS and lifestyle factors related to smoking and alcohol consumption. Conclusions The study demonstrated the potential of PRS-based PheWAS in revealing associations between genetic risk factors for HNSCC and various phenotypic traits. The findings emphasized the importance of considering genetic susceptibility in understanding HNSCC and highlighted shared genetic bases between HNSCC and other health conditions and lifestyles.

Abstract Background Previous studies have shown that lifestyle/environmental factors could accelerate the development of age-related hearing loss (ARHL). However, there has not yet been a study investigating the joint association among genetics, lifestyle/environmental factors, and adherence to healthy lifestyle for risk of ARHL. We aimed to assess the association between ARHL genetic variants, lifestyle/environmental factors, and adherence to healthy lifestyle as pertains to risk of ARHL. Methods This case–control study included 376,464 European individuals aged 40 to 69 years, enrolled between 2006 and 2010 in the UK Biobank (UKBB). As a replication set, we also included a total of 26,523 individuals considered of European ancestry and 9834 individuals considered of African-American ancestry through the Penn Medicine Biobank (PMBB). The polygenic risk score (PRS) for ARHL was derived from a sensorineural hearing loss genome-wide association study from the FinnGen Consortium and categorized as low, intermediate, high, and very high. We selected lifestyle/environmental factors that have been previously studied in association with hearing loss. A composite healthy lifestyle score was determined using seven selected lifestyle behaviors and one environmental factor. Results Of the 376,464 participants, 87,066 (23.1%) cases belonged to the ARHL group, and 289,398 (76.9%) individuals comprised the control group in the UKBB. A very high PRS for ARHL had a 49% higher risk of ARHL than those with low PRS (adjusted OR, 1.49; 95% CI, 1.36–1.62; P

Abstract Clinical decision support systems (CDSSs) play a critical role in enhancing the efficiency of mental health care delivery and promoting patient engagement. Transdiagnostic approaches that utilize raw psychological and biological data enable personalized patient profiling and treatment. This study introduces a CDSS incorporating symptom profiling and drug recommendation for mental health care. Among the UK Biobank cohort, we analyzed 157,348 participants for symptom profiling and 14,358 participants with a drug prescription history for drug recommendation. Among the 1307 patients in the Samsung Medical Center cohort, 842 were eligible for analysis. Symptom profiling utilized demographic and questionnaire data, employing conventional clustering and community detection methods. Identified clusters were explored using diagnostic mapping, feature importance, and scoring. For drug recommendation, we employed cluster- and network-based approaches. The analysis identified nine clusters using k-means clustering and ten clusters with the Louvain method. Clusters were annotated for distinct features related to depression, anxiety, psychosis, drug addiction, and self-harm. For drug recommendation, drug prescription probabilities were retrieved for each cluster. A recommended list of drugs, including antidepressants, antipsychotics, mood stabilizers, and sedative–hypnotics, was provided to individual patients. This CDSS holds promise for efficient personalized mental health care and requires further validation and refinement with larger datasets, serving as a valuable tool for mental healthcare providers.

Abstract Excessive activation of poly (ADP-ribose) polymerase (PARP) contributes to ischemic acute kidney injury (AKI). PARP inhibition has been shown to be beneficial in renal ischemia–reperfusion injury (IRI) in the early phase, but its role in the repair process remains unclear. The effects of JPI-289, a novel PARP inhibitor, during the healing phase after renal IRI were investigated. IRI was performed on 9-week-old male C57BL/6 mice. Saline or JPI-289 100 mg/kg was intraperitoneally administered once at 24 h or additionally at 48 h after IRI. Hypoxic HK-2 cells were treated with JPI-289. Renal function and fibrosis extent were comparable between groups. JPI-289 treatment caused more prominent tubular atrophy and proinflammatory intrarenal leukocyte phenotypes and cytokines/chemokines changes at 12 weeks after unilateral IRI. JPI-289 treatment enhanced gene expressions associated with collagen formation, toll-like receptors, and the immune system in proximal tubules and endothelial cells after IRI. JPI-289 treatment at 3 or 6 h after hypoxia facilitated proliferation of hypoxic HK-2 cells, whereas further treatment after 24 h suppressed proliferation. Delayed inhibition of PARP after renal IRI did not facilitate the repair process during the early healing phase but rather may aggravate renal tubular atrophy during the late healing phase in ischemic AKI.

Abstract In radiomics research, the issue of different instruments being used is significant. In this study, we compared three correction methods to reduce the batch effects in radiogenomic data from fluorodeoxyglucose (FDG) PET/CT images of lung cancer patients. Texture features of the FDG PET/CT images and genomic data were retrospectively obtained. The features were corrected with different methods: phantom correction, ComBat method, and Limma method. Batch effects were estimated using three analytic tools: principal component analysis (PCA), the k-nearest neighbor batch effect test (kBET), and the silhouette score. Finally, the associations of features and gene mutations were compared between each correction method. Although the kBET rejection rate and silhouette score were lower in the phantom-corrected data than in the uncorrected data, a PCA plot showed a similar variance. ComBat and Limma methods provided correction with low batch effects, and there was no significant difference in the results of the two methods. In ComBat- and Limma-corrected data, more texture features exhibited a significant association with the TP53 mutation than in those in the phantom-corrected data. This study suggests that correction with ComBat or Limma methods can be more effective or equally as effective as the phantom method in reducing batch effects.

Abstract Background Cyclin-dependent kinase 4/6 inhibitor (CDK4/6) therapy plus endocrine therapy (ET) is an effective treatment for patients with hormone receptor-positive/human epidermal receptor 2-negative metastatic breast cancer (HR+/HER2− MBC); however, resistance is common and poorly understood. A comprehensive genomic and transcriptomic analysis of pretreatment and post-treatment tumors from patients receiving palbociclib plus ET was performed to delineate molecular mechanisms of drug resistance. Methods Tissue was collected from 89 patients with HR+/HER2− MBC, including those with recurrent and/or metastatic disease, receiving palbociclib plus an aromatase inhibitor or fulvestrant at Samsung Medical Center and Seoul National University Hospital from 2017 to 2020. Tumor biopsy and blood samples obtained at pretreatment, on-treatment (6 weeks and/or 12 weeks), and post-progression underwent RNA sequencing and whole-exome sequencing. Cox regression analysis was performed to identify the clinical and genomic variables associated with progression-free survival. Results Novel markers associated with poor prognosis, including genomic scar features caused by homologous repair deficiency (HRD), estrogen response signatures, and four prognostic clusters with distinct molecular features were identified. Tumors with TP53 mutations co-occurring with a unique HRD-high cluster responded poorly to palbociclib plus ET. Comparisons of paired pre- and post-treatment samples revealed that tumors became enriched in APOBEC mutation signatures, and many switched to aggressive molecular subtypes with estrogen-independent characteristics. We identified frequent genomic alterations upon disease progression in RB1, ESR1, PTEN, and KMT2C. Conclusions We identified novel molecular features associated with poor prognosis and molecular mechanisms that could be targeted to overcome resistance to CKD4/6 plus ET. Trial registration ClinicalTrials.gov, NCT03401359. The trial was posted on 18 January 2018 and registered prospectively.

Abstract Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [n] of additional SNPs = 105), BD I (n = 54), MDD (n = 107), and irritability (n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.

Abstract Background Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. Methods We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. Results In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e−4 for progression-free survival (PFS) and 3.63e−4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fisher’s exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e−4 for PFS and 3.66e−4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient using in vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage ( http://www.wang-lab-hkust.com:3838/TMZEP ). Conclusions We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs.

Abstract Background Young patients with colorectal cancer (CRC) exhibit poor prognoses compared to older patients due to the difficulty in early diagnosis and treatment. However, the underlying molecular characteristics are still unclear. Methods We conducted a comprehensive analysis of 49 CRC patients without hereditary CRC using the whole-exome and RNA sequencing with tumor and matched normal samples. A total of 594 TCGA samples and 4 patient-derived cells were utilized for validation. Results Consensus molecular subtype 4 (CMS4) (53.85%) and CMS2 (38.46%) were enriched in the young (≤ 40 years) and old (> 60 years) age groups, respectively. A CMS4-associated gene, platelet-derived growth factor receptor α (PDGFRA), was significantly upregulated in young patients with CRC (FC = 3.21, p = 0.0001) and was negatively correlated with age (p = 0.0001, R = − 0.526). Moreover, PDGFRA showed a positive co-expression with metastasis-related genes in young CRC patients. In vitro validation confirmed that young patient-derived cells (PDCs) showed an enriched expression of PDGFRA compared to old PDCs and a reduced proliferation rate by knockdown of PDGFRA. Furthermore, young CRC patients were more sensitive to regorafenib, a PDGFRA-targeting drug, than old CRC patients. Conclusions Our study suggests that CRC in young patients is associated with CMS4 and PDGFRA. In addition, PDGFRA may serve potential of novel therapeutic strategies and represent a predictive biomarker of response to regorafenib for young CRC patients.

Abstract Previous studies suggested that genetic, environmental factors and their interactions could affect body fat mass (BFM). However, studies describing these effects were performed at a single time point in a population. In this study, we investigated the interaction between genetic and environmental factors in affecting BFM and implicate the healthcare utilization of lifestyle modifications from a personalized and genomic perspective. We examined how nutritional intake or physical activity changes in the individuals affect BFM concerning the genetic composition. We conducted an observational study including 259 adult participants with single nucleotide polymorphism (SNP) genotyping and longitudinal lifestyle monitoring, including food consumption and physical activities, by following lifestyle modification guidance. The participants’ lifelog data on exercise and diet were collected through a wearable device for 3 months. Moreover, we measured anthropometric and serologic markers to monitor their potential changes through lifestyle modification. We examined the influence of genetic composition on body fat reduction induced by lifestyle changes using genetic risk scores (GRSs) of three phenotypes: GRS-carbohydrate (GRS-C), GRS-fat (GRS-F), and GRS-exercise (GRS-E). Our results showed that lifestyle modifications affected BFM more significantly in the high GRS class compared to the low GRS class, indicating the role of genetic factors affecting the efficiency of the lifestyle modification-induced BFM changes. Interestingly, the influence of exercise modification in the low GRS class with active lifestyle change was lower than that in the high GRS class with inactive lifestyle change (P = 0.022), suggesting the implication of genetic factors for efficient body fat control.

Abstract We evaluated the predictive role of circulating tumor DNA (ctDNA) detection by targeted deep sequencing in patients with metastatic renal cell carcinoma (mRCC) treated with immune checkpoint blockades (ICB). To determine the feasibility of ctDNA detection in our panel encompassing 40 genes, we collected 10 ml of blood from 20 patients at the time of radical nephrectomy. We analyzed somatic mutations in primary tumors and ctDNA samples from these patients. We finally collected 10 ml of blood before and after 1 month of treatment, respectively, from four patients with mRCC who received first-line ICB treatment. Variants were detected in primary tumors of 15 patients (75%) and ctDNA was detected in the plasma of 9 patients (45%). We examined the predictive role of ctDNA in four patients who received first-line ICB therapy. In two patients showing partial response, ctDNA levels decreased after 1 month of ICB treatment. However, in one patient who showed disease progression, ctDNA levels increased after 1 month of ICB treatment. Taken together, ctDNA detection in plasma by targeted deep sequencing was feasible in patients with RCC. Moreover, the levels of ctDNA could be an early predictor of treatment response in patients with mRCC who receive ICB therapy.

Abstract The use of precision medicine for chemotherapy requires the individualization of the therapeutic regimen for each patient. This approach improves treatment efficacy and reduces the probability of administering ineffective drugs. To ensure accurate decision-making in a timely manner, anticancer drug efficacy tests must be performed within a short timeframe using a small number of cancer cells. These requirements can be satisfied via microfluidics-based drug screening platforms, which are composed of complex fluidic channels and closed systems. Owing to their complexity, skilled manipulation is required. In this study, we developed a microfluidic platform, to accurately perform multiple drug efficacy tests using a small number of cells, which can be conducted via simple manipulation. As it is a small, open-chamber system, a minimal number of cells could be loaded through simple pipetting. Furthermore, the extracellular matrix gel inside the chamber provides an in vivo-like environment that enables the localized delivery of the drugs to spontaneously diffuse from the channels underneath the chamber without a pump, thereby efficiently and robustly testing the efficacy and resistance of multiple drugs. We demonstrated that this platform enabled the rapid and facile testing of multiple drugs using a small number of cells (~ 10,000) over a short period of time (~ 2 days). These results provide the possibility of using this powerful platform for selecting therapeutic medication, developing new drugs, and delivering personalized medicine to patients.

Cancer chemotherapy: treatment prolongs resistance caused by DNA modification Cancer cells that are transiently resistant to drug therapies owing to changes in their gene expression patterns can become resistant for longer durations if exposed to the drug treatments. A team led by Kyeong-Man Hong and Hyonchol Jang from the National Cancer Center in Goyang, South Korea, used cellular reprogramming technologies to induce changes in the DNA markers that regulate gene expression. Working with lung and gastric cancer cell lines, the researchers found that such epigenetic alterations caused many cells to become resistant to the chemotherapy drugs cisplatin and paclitaxel. In the absence of treatment, the cells soon lost their drug resistance. In the presence of the chemotherapeutics, however, the resistance trait lasted longer, a finding that could inform best practice for how to administer cancer-fighting agents in the face of epigenetic-driven drug resistance.

Abstract Background Tumor cell-intrinsic mechanisms and complex interactions with the tumor microenvironment contribute to therapeutic failure via tumor evolution. It may be possible to overcome treatment resistance by developing a personalized approach against relapsing cancers based on a comprehensive analysis of cell type-specific transcriptomic changes over the clinical course of the disease using single-cell RNA sequencing (scRNA-seq). Methods Here, we used scRNA-seq to depict the tumor landscape of a single case of chemo-resistant metastatic, muscle-invasive urothelial bladder cancer (MIUBC) addicted to an activating Harvey rat sarcoma viral oncogene homolog (HRAS) mutation. In order to analyze tumor evolution and microenvironmental changes upon treatment, we also applied scRNA-seq to the corresponding patient-derived xenograft (PDX) before and after treatment with tipifarnib, a HRAS-targeting agent under clinical evaluation. Results In the parallel analysis of the human MIUBC and the PDX, diverse stromal and immune cell populations recapitulated the cellular composition in the human and mouse tumor microenvironment. Treatment with tipifarnib showed dramatic anticancer effects but was unable to achieve a complete response. Importantly, the comparative scRNA-seq analysis between pre- and post-tipifarnib-treated PDX revealed the nature of tipifarnib-refractory tumor cells and the tumor-supporting microenvironment. Based on the upregulation of programmed death-ligand 1 (PD-L1) in surviving tumor cells, and the accumulation of multiple immune-suppressive subsets from post-tipifarnib-treated PDX, a PD-L1 inhibitor, atezolizumab, was clinically applied; this resulted in a favorable response from the patient with acquired resistance to tipifarnib. Conclusion We presented a single case report demonstrating the power of scRNA-seq for visualizing the tumor microenvironment and identifying molecular and cellular therapeutic targets in a treatment-refractory cancer patient.

Abstract Background While auditory neuropathy spectrum disorder (ANSD) is a heterogeneous disorder and its management quite varies depending upon the etiology, even including self-resolution, OTOF is an important molecular etiology of prelingual ANSD and has emerged as an attractive target for implementation of precision medicine in terms of timing and prognosis prediction of auditory rehabilitation. However, to date, the literature is lacking in the genotype–phenotype relationship of this gene as well as efficient molecular testing strategy in the clinic in many populations and to make things more complicated in Koreans, the most prevalent variant p.Arg1939Gln among Korean ANSD children frequently evaded detection by next generation sequencing (NGS), resulting in delayed genetic diagnosis and late cochlear implantation (CI). The aims of this study are to document the mutational and phenotypic spectrum of OTOF-related ANSD (DFNB9) in the Korean population, further establishing genotype–phenotype correlation and proposing a set of the most commonly found OTOF variants to be screened first. Methods Genetic diagnosis through the NGS-based sequencing was made on patients with ANSD in two tertiary hospitals. Genotype and phenotypes of eleven DFNB9 patients were reviewed. For data analysis, Mann–Whitney test and Fisher’s exact test were applied. Results This study disclosed four prevalent variants in Koreans: p.Arg1939Gln with an allele frequency of 40.9%, p.Glu841Lys (13.6%), p.Leu1011Pro and p.Arg1856Trp (9.1%). Three novel variants (c.4227 + 5G > C, p.Gly1845Glu, and p.Pro1931Thr) were identified. Interestingly, a significant association of p.Arg1939Gln with worse ASSR thresholds was observed despite consistently no ABR response. Ten of 11 DFNB9 patients received CI for auditory rehabilitation, showing favorable outcomes with more rapid improvement on early-CI group (age at CI ≤ 18 mo.) than late-CI group. Conclusions This study included the largest Korean DFNB9 cohort to date and proposed a set of the most frequent four OTOF variants, allowing the potential prioritization of exons during Sanger sequencing. Further, a significant association of p.Arg1939Gln homozygotes with poor residual hearing was observed. We may have to suspect p.Arg1939Gln homozygosity in cases of poor auditory thresholds in ANSD children with putative negative OTOF variants solely screened by NGS. Reciprocal feedback between bench and clinics regarding DFNB9 would complement each other.

Purpose Neurotropic tropomyosin receptor kinase (NTRK) fusions have been identified in a variety of cancers, and tyrosine kinase inhibitors targeting the tropomyosin receptor kinase (TRK) receptor are currently in clinical trials. However, no reports are available on the effects of NTRK gene amplification. Methods Samples from patients enrolled in the sequencing program were analyzed using a next-generation sequencing (NGS) cancer panel. For cases in which NTRK amplification (defined as ≥ 4.0 copies) was identified, panTRK immunohistochemical (IHC) staining of tissue microarrays was performed. Results A total of 1,250 tumor specimens collected between February 2014 and January 2016 were analyzed using the NGS cancer panel. NTRK amplification was detected in 28 cases of various types of cancer. Among 27 cases, only four were positive for pan-TRK IHC. These four cases were melanoma, sarcoma, lung cancer, and gastric cancer. We found that 2.2% of cancer patients showed NTRK amplification using NGS cancer panel and NTRK amplification resulted in protein overexpression in 14.8% of these patients. Conclusion Patients with NTRK amplification and increased TRK protein expression may be considered for inclusion in clinical trials for NTRK inhibitors.

Abstract Despite efforts to interrogate human genome variation through large-scale databases, systematic preference toward populations of Caucasian descendants has resulted in unintended reduction of power in studying non-Caucasians. Here we report a compilation of coding variants from 1,055 healthy Korean individuals (KOVA; Korean Variant Archive). The samples were sequenced to a mean depth of 75x, yielding 101 singleton variants per individual. Population genetics analysis demonstrates that the Korean population is a distinct ethnic group comparable to other discrete ethnic groups in Africa and Europe, providing a rationale for such independent genomic datasets. Indeed, KOVA conferred 22.8% increased variant filtering power in addition to Exome Aggregation Consortium (ExAC) when used on Korean exomes. Functional assessment of nonsynonymous variant supported the presence of purifying selection in Koreans. Analysis of copy number variants detected 5.2 deletions and 10.3 amplifications per individual with an increased fraction of novel variants among smaller and rarer copy number variable segments. We also report a list of germline variants that are associated with increased tumor susceptibility. This catalog can function as a critical addition to the pre-existing variant databases in pursuing genetic studies of Korean individuals.

Abstract Somatic mutations in cancer genomes often show allelic imbalance (AI) of mutation abundance between the genome and transcriptome, but there is not yet a systematic understanding of AI. In this study, we performed large-scale DNA and RNA AI analyses of >100,000 somatic mutations in >2,000 cancer specimens across five tumor types using the exome and transcriptome sequencing data of the Cancer Genome Atlas consortium. First, AI analysis of nonsense mutations and frameshift indels revealed that nonsense-mediated decay is typical in cancer genomes, and we identified the relationship between the extent of AI and the location of mutations in addition to the well-recognized 50-nt rules. Second, the AI with splice site mutations may reflect the extent of intron retention and is frequently observed in known tumor suppressor genes. For missense mutations, we observed that mutations frequently subject to AI are enriched to genes related to cancer, especially those of apoptosis and the extracellular matrix, and C:G > A:T transversions. Our results suggest that mutations in known cancer-related genes and their transcripts are subjected to different levels of transcriptional or posttranscriptional regulation compared to wildtype alleles and may add an additional regulatory layer to the functions of cancer-relevant genes.

Advances in genomic technologies and the development of targeted therapeutics are making the use of precision medicine increasingly possible. In this study, we explored whether precision medicine can be applied for the management of refractory/relapsed pediatric solid tumors by discovering actionable alterations using targeted panel sequencing. Samples of refractory/relapsed pediatric solid tumors were tested using a targeted sequencing panel covering the exonic DNA sequences of 381 cancer genes and introns across 22 genes to detect clinically significant genomic aberrations in tumors. The molecular targets were tiered from 1 to 5 based on the presence of actionable genetic alterations, strength of supporting evidence, and drug availability in the Republic of Korea. From January 2016 to October 2018, 55 patients were enrolled. The median time from tissue acquisition to drug selection was 29 d (range 14-39), and tumor profiling was successful in 53 (96.4%) patients. A total of 27 actionable alterations in tiers 1-4 were detected in 20 patients (36.4%), and the majority of actionable alterations were copy number variations. The tiers of molecular alterations were tier 1 (clinical evidence) in 4 variants, tier 2 (preclinical evidence) in 8 variants, tier 3 (consensus opinion) in 2 variants, and tier 4 (actionable variants with a drug that is available in other countries but not in the Republic of Korea) in 9 variants. In one patient with relapsed neuroblastoma with ALK F1174L mutation and ALK amplification, lorlatinib was used in a compassionate use program, and it showed some efficacy. In conclusion, using a targeted sequencing panel to discover actionable alterations in relapsed/refractory pediatric solid tumors was practical and feasible.

Intratumoral heterogeneity (ITH) refers to the presence of distinct tumor cell populations. It provides vital information for the clinical prognosis, drug responsiveness, and personalized treatment of cancer patients. As genomic ITH in various cancers affects the expression patterns of genes, the expression profile could be utilized for determining ITH level. Herein, we present a novel approach to directly detect high ITH defined as a larger number of subclones from the gene expression pattern through machine learning approaches. We examined associations between gene expression profile and ITH of 12 cancer types from The Cancer Genome Atlas (TCGA) database. Using stomach adenocarcinoma (STAD) showing high association, we evaluated the performance of our method in predicting ITH by employing three machine learning algorithms using gene expression profile data. We classified tumors into high and low heterogeneity groups using the learning model through the selection of LASSO feature. The result showed that support vector machines (SVMs) outperformed other algorithms (AUC = 0.84 in SVMs and 0.82 in Naïve Bayes) and we were able to improve predictive power by using both combined data from mutation and expression. Furthermore, we evaluated the prediction ability of each model using simulation data generated by mixing cell lines of the Cancer Cell Line Encyclopedia (CCLE), and obtained consistent results with using real dataset. Our approach could be utilized for discriminating tumors with heterogeneous cell populations to characterize ITH.

Alternative polyadenylation (APA) in 3' untranslated regions (3' UTR) plays an important role in regulating transcript abundance, localization, and interaction with microRNAs. Length-variation of 3'UTRs by APA contributes to efficient proliferation of cancer cells. In this study, we investigated APA in single cancer cells and tumor microenvironment cells to understand the physiological implication of APA in different cell types. We analyzed APA patterns and the expression level of genes from the 515 single-cell RNA sequencing (scRNA-seq) dataset from 11 breast cancer patients. Although the overall 3'UTR length of individual genes was distributed equally in tumor and non-tumor cells, we found a differential pattern of polyadenylation in gene sets between tumor and non-tumor cells. In addition, we found a differential pattern of APA across tumor types using scRNA-seq data from 3 glioblastoma patients and 1 renal cell carcinoma patients. In detail, 1,176 gene sets and 53 genes showed the distinct pattern of 3'UTR shortening and over-expression as signatures for five cell types including B lymphocytes, T lymphocytes, myeloid cells, stromal cells, and breast cancer cells. Functional categories of gene sets for cellular proliferation demonstrated concordant regulation of APA and gene expression specific to cell types. The expression of APA genes in breast cancer was significantly correlated with the clinical outcome of earlier stage breast cancer patients. We identified cell type-specific APA in single cells, which allows the identification of cell types based on 3'UTR length variation in combination with gene expression. Specifically, an immune-specific APA signature in breast cancer could be utilized as a prognostic marker of early stage breast cancer.