Higher Tumor Mutation Burden Level Research Articles

Predictive value of immediate early response 5 like (IER5L) in the prognosis and immune checkpoint blockade therapy of non-small cell lung cancer patients

BackgroundNon-small cell lung cancer (NSCLC) is a malignancy with high mortality. Immediate early response 5 like (IER5L) has been found to associate with worse prognosis in colorectal cancer patients. However, its role in the prognosis prediction of NSCLC has remained largely unknown. MethodsThe IER5L expression in NSCLC and normal tissues was analyzed in two public cohorts: TCGA-LUAD-LUSC and GSE159857. Additionally, functional enrichment, survival analysis, CIBERSORT and tumor mutation burden (TMB) were investigated between low- and high-IER5L level groups. The in vitro IER5L mRNA and protein levels were determined using RT-qPCR and western blot, respectively. ResultsThe data from TCGA-LUAD-LUSC and GSE159857 cohorts showed a high IER5L mRNA expression in NSCLC tissue samples compared to normal controls. The increased expression of IER5L in NSCLC cells were also validated by RT-qPCR and western blot analysis. Additionally, NSCLC patients with high-IER5L level had significantly worse prognosis and IER5L could be used as an independent prognostic factor for NSCLC patients. Meanwhile, patients in the high-IER5L group had higher TMB level. IER5L expression was negatively correlated with the proportion of Monocytes and T cells CD4 memory resting, and was positively related to the proportion of Tregs and M0 macrophages in tumor tissues. Besides, transcription factors TFAP4 and ZNF692 may bind to the promoter region of IER5L, and then modulate IER5L gene transcription, thereby affecting IER5L gene expression. Furthermore, GSEA results showed that IER5L gene was closely related to MAPK, PI3K-Akt, NF-kappaB signaling pathways in NSCLC. ConclusionCollectively, high IER5L expression may be a promising unfavorable prognostic biomarker and therapeutic target for NSCLC patients.

SDPS-28 THE STUDY OF AN ANOIKIS-RELATED SIGNATURE TO PREDICT GLIOMA PROGNOSIS AND IMMUNE INFILTRATION

Abstract BACKGROUND Gliomas are the most common highly aggressive primary malignant brain tumors in adults with different biological behavior and clinically heterogeneous features. Method: We extracted the anoikis-related genes (ARGs) from GeneCards and obtained differentially expressed genes in normal and glioma tissues from the GSE4290 dataset by differential analysis to obtain intersect differentially expressed ARG in gliomas. KEGG and GO analysis were used to evaluate the potential pathways and molecular processes of these genes. Based on The Cancer Genome Atlas (TCGA) training cohort, we performed the Least Absolute Shrinkage and Selection Operator (LASSO) regression and Cox regression to construct an ARG prognostic model and validated them in the TCGA testing cohort and the Chinese Glioma Genome Atlas (CGGA) validation cohort. Subsequently, we further explored the differences in clinical characteristics, tumor mutation burden(TMB), and the immune microenvironment in the high- and low-risk groups. Univariate and multifactorial regression analyses and nomogram construction were also performed. Moreover, we assessed the expression levels and clinical prognostic value of prognostic key genes. RESULTS The regulatory model based on quantitative ARG prognostic models showed that patients in the high-risk group were associated with poorer survival prognosis, poorer clinical characteristics, and higher TMB levels. Moreover, the high-risk group had high levels of immune infiltration and upregulated immune checkpoint gene expression. The ARG prognostic model and the Nomogram showed good predictive performance. Expression and survival analysis of five prognostic ARG signatures (ETV4, HMOX1, MYC, NFE2L2, and UBE2C) showed that these genes except MYC were cancer-promoting genes. CONCLUSION Our constructed ARG prognostic risk model provides a potential therapeutic target and theoretical basis for predicting the prognosis of glioma patients and guiding individualized immunotherapy.

The study of an anoikis-related signature to predict glioma prognosis and immune infiltration.

Gliomas are the most common highly aggressive primary malignant brain tumors in adults with different biological behaviors and clinically heterogeneous features. About the extremely poor prognosis of gliomas, the search for potential therapeutic modalities and targets is crucial. We extracted the anoikis-related genes (ARG) from GeneCards and obtained differentially expressed genes in normal and glioma tissues from the GSE4290 dataset to obtain intersect differentially expressed ARG in gliomas by differential analysis. KEGG and GO analyses were used to evaluate the potential pathways and molecular processes of these genes. Based on The Cancer Genome Atlas (TCGA) training cohort, we performed the Least Absolute Shrinkage and Selection Operator (LASSO) regression and Cox regression to construct an ARG prognostic model and validated them in the TCGA testing cohort and the Chinese Glioma Genome Atlas (CGGA) validation cohort. Subsequently, we further explored the differences in clinical characteristics, tumor mutation burden (TMB), and the immune microenvironment in the high- and low-risk groups. Univariate and multifactorial regression analyses and nomogram construction were also performed. Moreover, we evaluated the expression levels of key genes via public databases, qPCR analysis and IHC staining, and further assessed the clinical prognostic value. The regulatory model based on quantitative ARG prognostic models showed that patients in the high-risk group were associated with poorer survival prognosis, poorer clinical characteristics, and higher TMB levels. Moreover, the high-risk group had high levels of immune infiltration and upregulated immune checkpoint gene expression. The ARG prognostic model and the Nomogram showed good predictive performance. Expression and survival analysis of five prognostic ARG signatures (ETV4, HMOX1, MYC, NFE2L2, and UBE2C) showed that these genes have potential prognostic value. Our constructed ARG prognostic risk model provides a potential therapeutic target and theoretical basis for predicting the prognosis of glioma patients and guiding individualized immunotherapy.

A cuproptosis-related LncRNA signature: Integrated analysis associated with biochemical recurrence and immune landscape in prostate cancer.

Background: As a new form of regulated cell death, cuproptosis differs profoundly from apoptosis, ferroptosis, pyroptosis, and necroptosis. The correlation between cuproptosis and long non-coding RNAs (lncRNAs) has been increasingly studied recently. In this study, a novel cuproptosis-related lncRNA prognostic signature was developed to investigate biochemical recurrence (BCR) and tumor immune landscape in prostate cancer (PCa). Methods and Materials: The transcriptome data and clinicopathologic information of PCa patients were downloaded from The Cancer Genome Atlas (TCGA). Pearson's correlation analysis was applied to identify lncRNAs associated with cuproptosis. Based on Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression analysis, we developed a cuproptosis-related lncRNA prognostic model (risk score) to predict the BCR of PCa patients. Additionally, we also constructed a nomogram with the risk score and clinicopathologic features. The biological function, tumor mutation burden (TMB), immune cell infiltration, expression levels of immune checkpoint genes, and anti-cancer drug sensitivity were investigated. Results: We constructed and validated the cuproptosis-related lncRNA signature prognostic model (risk score) by six crlncRNAs. All patients were divided into the low- and high-risk groups based on the median risk score. The Kaplan-Meier (KM) survival analysis revealed that the high-risk group had shorter BCR-free survival (BCRFS). The risk score has been proven to be an independent prognostic factor of BCR in PCa patients. In addition, a nomogram of risk scores and clinicopathologic features was established and demonstrated an excellent predictive capability of BCR. The ROC curves further validated that this nomogram had higher accuracy of predicting the BCR compared to other clinicopathologic features. We also found that the high-risk group had higher TMB levels and more infiltrated immune cells. Furthermore, patients with high TMB in the high-risk group were inclined to have the shortest BCRFS. Finally, patients in the high-risk group were more susceptible to docetaxel, gefitinib, methotrexate, paclitaxel, and vinblastine. Conclusion: The novel crlncRNA signature prognostic model shows a greatly prognostic prediction value of BCR for PCa patients, extends our thought on the association of cuproptosis and PCa, and provides novel insights into individual-based treatment strategies for PCa.

Construction of a pyroptosis-related lncRNAs signature for predicting prognosis and immunotherapy response in glioma.

Recent studies have proved that pyroptosis-related long non-coding RNAs (PRlncRNAs) are closely linked to tumor progression, prognosis, and immunity. Here, we systematically evaluated the correlation of PRlncRNAs with glioma prognosis. This study included 3 glioma cohorts (The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and Gravendeel). Through Pearson correlation analysis, PRlncRNAs were screened from these 3 cohorts. Univariate Cox regression analysis was then carried out to determine the prognostic PRlncRNAs. A pyroptosis-related lncRNAs signature (PRLS) was then built by least absolute shrinkage and selection operator and multivariate Cox analyses. We systematically evaluated the correlation of the PRLS with the prognosis, immune features, and tumor mutation burden in glioma. A total of 14 prognostic PRlncRNAs overlapped in all cohorts and were selected as candidate lncRNAs. Based on The Cancer Genome Atlas cohort, a PRLS containing 7 PRlncRNAs was built. In all cohorts, the PRLS was proved to be a good predictor of glioma prognosis, with a higher risk score related to a poorer prognosis. We observed obvious differences in the immune microenvironment, immune cell infiltration level, and immune checkpoint expression in low- and high-risk subgroups. Compared with low-risk cases, high-risk cases had lower Tumor Immune Dysfunction and Exclusion scores and greater tumor mutation burden, indicating that high-risk cases can be more sensitive to immunotherapy. A nomogram combining PRLS and clinical parameters was constructed, which showed more robust and accurate predictive power. In conclusion, the PRLS is a potentially useful indicator for predicting prognosis and response to immunotherapy in glioma. Our findings may provide a useful insight into clinically individualized treatment strategies for patients.

Comparative study of the genomic landscape and tumor microenvironment among large cell carcinoma of the lung, large cell neuroendocrine of the lung, and small cell lung cancer.

Deciphering the genomic profiles and tumor microenvironment (TME) in large cell carcinomas of the lung (LCC), large cell neuroendocrine of the lung (LCNEC), and small cell lung cancer (SCLC) might contribute to a better understanding of lung cancer and then improve outcomes. Ten LCC patients, 12 LCNEC patients, and 18 SCLC patients were enrolled. Targeted next-generation sequencing was used to investigate the genomic profiles of LCC, LCNEC, and SCLC. Tumor-infiltrating lymphocytes (TILs) within cancer cell nests and in cancer stroma were counted separately. Precise 60% of LCNEC patients harbored classical non-small cell lung cancer driver alterations, occurring in BRAF, KRAS, ROS1, and RET. More than 70% of SCLC patients harbored TP53-RB1 co-alterations. Moreover, 88.9%, 40%, and 77.8% of LCC, LCNEC, and SCLC cases had a high tumor mutation burden level with more than 7 mutations/Mb. Furthermore, high index of CD68+ CD163+ (TILs within cancer cell nests/ TILs within cancer cell nests and in cancer stroma, P = .041, 548 days vs not reached) and CD163+ TILs (P = .041, 548 days vs not reached) predicted a shorter OS in SCLC. Our findings revealed the distinct genomic profiles and TME contexture among LCC, LCNEC, and SCLC. Our findings suggest that stratifying LCNEC/SCLC patients based on TME contexture might help clinical disease management.

Effects of Lipid Metabolism-Related Genes PTGIS and HRASLS on Phenotype, Prognosis, and Tumor Immunity in Lung Squamous Cell Carcinoma.

Lipid metabolism reprogramming played an important role in cancer occurrence, development, and immune regulation. The aim of this study was to identify and validate lipid metabolism-related genes (LMRGs) associated with the phenotype, prognosis, and immunological characteristics of lung squamous cell carcinoma (LUSC). In the TCGA cohort, bioinformatics and survival analysis were used to identify lipid metabolism-related differentially expressed genes (DEGs) associated with the prognosis of LUSC. PTGIS/HRASLS knockdown and overexpression effects on the LUSC phenotype were analyzed in vitro experiments. Based on the expression distribution of PTGIS/HRASLS, LUSC patients were divided into two clusters by consensus clustering. Clinical information, prognosis, immune infiltration, expression of immune checkpoints, and tumor mutation burden (TMB) level were compared between the TCGA and GSE4573 cohorts. The genes related to clustering and tumor immunity were screened by weighted gene coexpression network analysis (WGCNA), and the target module genes were analyzed by functional enrichment analysis, protein-protein interaction (PPI) analysis, and immune correlation analysis. 191 lipid metabolism-related DEGs were identified, of which 5 genes were independent prognostic genes of LUSC. PTGIS/HRASLS were most closely related to LUSC prognosis and immunity. RT-qPCR, western blot (WB) analysis, and immunohistochemistry (IHC) showed that the expression of PTGIS was low in LUSC, while HRASLS was high. Functionally, PTGIS promoted LUSC proliferation, migration, and invasion, while HRASLS inhibited LUSC proliferation, migration, and invasion. The two clusters' expression and distribution of PTGIS/HRASLS had the opposite trend. Cluster 1 was associated with lower pathological staging (pT, pN, and pTNM stages), better prognosis, stronger immune infiltration, higher expression of immune checkpoints, and higher TMB level than cluster 2. WGCNA found that 28 genes including CD4 and IL10RA were related to the expression of PTGIS/HRASLS and tumor immune infiltration. PTGIS/HRASLS in the GSE4573 cohort had the same effect on LUSC prognosis and tumor immunity as the TCGA cohort. PTGIS and HRASLS can be used as new therapeutic targets for LUSC as well as biomarkers for prognosis and tumor immunity, which has positive significance for guiding the immunotherapy of LUSC.

A cuproptosis-associated long non-coding RNA signature for the prognosis and immunotherapy of lung squamous cell carcinoma.

Cuproptosis, a copper-induced mechanism of mitochondrial-related cell death, has been implicated as a breakthrough in the treatment of cancer and has become a new treatment strategy. Furthermore, long non-coding RNA (lncRNA) can change the biological activities of tumor cells. Worldwide, lung squamous cell carcinoma (LUSC) is among the most common annoying tumors. LncRNAs related to cuproptosis are not researched at LUSC. Our research intends to develop a signature on the basis of cuproptosis-associated lncRNAs, which can predict LUSC prognosis and investigate LUSC immunological features. The TCGA database was used to retrieve LUSC transcriptome, clinical, and gene mutation data. For statistical analysis, we utilized the R program. We created a signature consisting of three cuproptosis-related lncRNAs in this investigation (including AC002467.1, LINC01740, and LINC02345). Survival analyses and Receiver Operating Characteristic curves demonstrated that this signature possessed powerful predictive capability. The signature's ability to predict was confirmed by a Receiver Operating Characteristic curve and principal component analysis. Notably, the patient with a high-risk score and a high tumor mutation burden level had a lower survival time. Furthermore, the tumor immune dysfunction and exclusion analysis showed that these individuals with low-risk scores may benefit from immunotherapy. The signature constructed by three cuproptosis-associated lncRNAs may be prognostic markers of LUSC. It contributes to immunotherapy and offers LUSC's therapy a new treatment direction.

A cuproptosis-associated long non-coding RNA signature for the prognosis and immunotherapy of lung squamous cell carcinoma.

Cuproptosis, a copper-induced mechanism of mitochondrial-related cell death, has been implicated as a breakthrough in the treatment of cancer and has become a new treatment strategy. Furthermore, long non-coding RNA (lncRNA) can change the biological activities of tumor cells. Worldwide, lung squamous cell carcinoma (LUSC) is among the most common annoying tumors. LncRNAs related to cuproptosis are not researched at LUSC. Our research intends to develop a signature on the basis of cuproptosis-associated lncRNAs, which can predict LUSC prognosis and investigate LUSC immunological features. The TCGA database was used to retrieve LUSC transcriptome, clinical, and gene mutation data. For statistical analysis, we utilized the R program. We created a signature consisting of three cuproptosis-related lncRNAs in this investigation (including AC002467.1, LINC01740, and LINC02345). Survival analyses and Receiver Operating Characteristic curves demonstrated that this signature possessed powerful predictive capability. The signature's ability to predict was confirmed by a Receiver Operating Characteristic curve and principal component analysis. Notably, the patient with a high-risk score and a high tumor mutation burden level had a lower survival time. Furthermore, the tumor immune dysfunction and exclusion analysis showed that these individuals with low-risk scores may benefit from immunotherapy. The signature constructed by three cuproptosis-associated lncRNAs may be prognostic markers of LUSC. It contributes to immunotherapy and offers LUSC's therapy a new treatment direction.

Genomic Alterations and Tumor Mutation Burden in Merkel Cell Carcinoma

Merkel cell carcinoma (MCC) is a rare and highly aggressive cutaneous neuroendocrine carcinoma with increasing incidence. Cytotoxic chemotherapy and checkpoint inhibitors provide treatment options in the metastatic setting; however, there are no approved or standard of care targeted therapy treatment options. To identify actionable alterations annotated by the OncoKB database therapeutic evidence level in association with tumor mutation burden (TMB). This is a retrospective, cross-sectional study using data from the American Association for Cancer Research Genomics Evidence Neoplasia Information Exchange, a multicenter international cancer consortium database. Patients with MCC were enrolled in participating institutions between 2017 and 2022. Data from version 11.0 of the database were released in January 2022 and analyzed from April to June 2022. The main outcome was the percentage of patients with high TMB and OncoKB level 3B and 4 alterations. A total of 324 tumor samples from 313 patients with MCC (107 women [34.2%]; 287 White patients [91.7%]; 7 Black patients [2.2%]) were cataloged in the database. The median (range) number of alterations was 4.0 (0.0-178.0), with a mean (SD) of 13.6 (21.2) alterations. Oncogenic alterations represented 20.2% of all alterations (862 of 4259 alterations). Tissue originated from primary tumor in 55.0% of patients (172 patients) vs metastasis in 39.6% (124 patients). TMB-high (≥10 mutations per megabase) was present in 26.2% of cases (82 patients). Next-generation sequencing identified 55 patients (17.6%) with a level 3B variation for a Food and Drug Administration-approved drug for use in a biomarker-approved indication or approved drug in another indication. An additional 8.6% of patients (27 patients) had a level 4 variation. Actionable alterations were more common among high TMB cases, with 37 of 82 patients (45.1%) harboring level 3 alterations compared with only 18 of 231 patients (7.8%) with low TMB. The most common level 3B gene variants included PIK3CA (12 patients [3.8%]), BRCA1/2 (13 patients [4.2%]), ATM (7 patients [2.2%]), HRAS (5 patients [1.6%]), and TSC1/2 (6 patients [1.9%]). The most common level 4 variants include PTEN (13 patients [4.1%]), ARID1A (9 patients [2.9%]), NF1 (7 patients [2.2%]), and CDKN2A (7 patients [2.2%]). Copy number alterations and fusions were infrequent. In 61.0% of cases (191 cases), a PanCancer pathway was altered, and 39.9% (125 cases) had alterations in multiple pathways. Commonly altered pathways were RTK-RAS (119 patients [38.0%]), TP53 (103 patients [32.9%]), cell cycle (104 patients [33.2%]), PI3K (99 patients [31.6%]), and NOTCH (93 patients [29.7%]). In addition, oncogenic DNA mismatch repair gene alterations were present in 8.0% of cases (25 patients). In this cross-sectional retrospective study of alterations and TMB in MCC, a minority of patients had potentially actionable alterations. These findings support the investigation of targeted therapies as single agent or in combination with immunotherapy or cytotoxic chemotherapy in selected MCC populations.

Identifying predictive biomarkers of apatinib in third-line treatment of advanced colorectal cancer through comprehensive genomic profiling.

Apatinib is a selective inhibitor of vascular endothelial growth factor receptor-2. Despite encouraging anticancer activity in different cancer types, some patients may not benefit from apatinib treatment. Herein, we characterized genomic profiles in colorectal cancer (CRC) patients to explore predictive biomarkers of apatinib at molecular level. We retrospectively recruited 19 CRC patients receiving apatinib as third-line treatment. Tissue samples before apatinib treatment were collected and subjected to genomic profiling using a targeted sequencing panel covering 520 cancer-related genes. After apatinib treatment, the patients achieved an objective response rate of 21% (4/19) and disease control rate of 57.9% (11/19). The median progression-free survival (PFS) and overall survival were 5 and 8.7 months, respectively. Genetic alterations were frequently identified in TP53 (95%), APC (53%), KRAS (53%) and PIK3CA (26%). Higher tumor mutation burden levels were significantly observed in patients harboring alterations in ERBB and RAS signaling pathways. Patients harboring FLT1 amplifications ( n = 3) showed significantly worse PFS than wild-type patients. Our study described molecular profiles in CRC patients receiving apatinib treatment and identified FLT1 amplification as a potential predictive biomarker for poor efficacy of apatinib. Further studies are warranted to validate the use of FLT1 amplification during apatinib treatment.

A novel cuproptosis-related lncRNA signature predicts the prognosis and immune landscape in bladder cancer.

Bladder cancer (BLCA) is one of the deadliest diseases, with over 550,000 new cases and 170,000 deaths globally every year. Cuproptosis is a copper-triggered programmed cell death and is associated with the prognosis and immune response of various cancers. Long non-coding RNA (lncRNA) could serve as a prognostic biomarker and is involved in the progression of BLCA. The gene expression profile of cuproptosis-related lncRNAs was analyzed by using data from The Cancer Genome Atlas. Cox regression analysis and least absolute shrinkage and selection operator analysis were performed to construct a cuproptosis-related lncRNA prognostic signature. The predictive performance of this signature was verified by ROC curves and a nomogram. We also explored the difference in immune-related activity, tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE), and drug sensitivity between the high- and low-risk groups. We successfully constructed a cuproptosis-related lncRNA prognostic signature for BLCA including eight lncRNAs (RNF139-AS1, LINC00996, NR2F2-AS1, AL590428.1, SEC24B-AS1, AC006566.1, UBE2Q1-AS1, and AL021978.1). Multivariate Cox analysis suggested that age, clinical stage, and risk score were the independent risk factors for predicting prognosis of BLCA. Further analysis revealed that this signature not only had higher diagnostic efficiency compared to other clinical features but also had a good performance in predicting the 1-year, 3-year, and 5-year overall survival rate in BLCA. Notably, BLCA patients with a low risk score seemed to be associated with an inflamed tumor immune microenvironment and had a higher TMB level than those with a high risk score. In addition, patients with a high risk score had a higher TIDE score and a higher half maximal inhibitory concentration value of many therapeutic drugs than those with a low risk score. We identified a novel cuproptosis-related lncRNA signature that could predict the prognosis and immune landscape of BLCA.

Construction of a cancer-associated fibroblasts-related long non-coding RNA signature to predict prognosis and immune landscape in pancreatic adenocarcinoma.

Background: Cancer-associated fibroblasts (CAFs) are an essential cell population in the pancreatic cancer tumor microenvironment and are extensively involved in drug resistance and immune evasion mechanisms. Long non-coding RNAs (lncRNAs) are involved in pancreatic cancer evolution and regulate the biological behavior mediated by CAFs. However, there is a lack of understanding of the prognostic signatures of CAFs-associated lncRNAs in pancreatic cancer patients. Methods: Transcriptomic and clinical data for pancreatic adenocarcinoma (PAAD) and the corresponding mutation data were obtained from The Cancer Genome Atlas database. lncRNAs associated with CAFs were obtained using co-expression analysis. lncRNAs were screened by Cox regression analysis using least absolute shrinkage and selection operator (LASSO) algorithm for constructing predictive signature. According to the prognostic model, PAAD patients were divided into high-risk and low-risk groups. Kaplan-Meier analysis was used for survival validation of the model in the training and validation groups. Clinicopathological parameter correlation analysis, univariate and multivariate Cox regression, time-dependent receiver operating characteristic (ROC) curves, and nomogram were performed to evaluate the model. The gene set variation analysis (GSVA) and gene ontology (GO) analyses were used to explore differences in the biological behavior of the risk groups. Furthermore, single-sample gene set enrichment analysis (ssGSEA), tumor mutation burden (TMB), ESTIMATE algorithm, and a series of immune correlation analyses were performed to investigate the relationship between predictive signature and the tumor immune microenvironment and screen for potential responders to immune checkpoint inhibitors. Finally, drug sensitivity analyses were used to explore potentially effective drugs in high- and low-risk groups. Results: The signature was constructed with seven CAFs-related lncRNAs (AP005233.2, AC090114.2, DCST1-AS1, AC092171.5, AC002401.4, AC025048.4, and CASC8) that independently predicted the prognosis of PAAD patients. Additionally, the high-risk group of the model had higher TMB levels than the low-risk group. Immune correlation analysis showed that most immune cells, including CD8+ T cells, were negatively correlated with the model risk scores. ssGSEA and ESTIMATE analyses further indicated that the low-risk group had a higher status of immune cell infiltration. Meanwhile, the mRNA of most immune checkpoint genes, including PD1 and CTLA4, were highly expressed in the low-risk group, suggesting that this population may be “hot immune tumors” and have a higher sensitivity to immune checkpoint inhibitors (ICIs). Finally, the predicted half-maximal inhibitory concentrations of some chemical and targeted drugs differ between high- and low-risk groups, providing a basis for treatment selection. Conclusion: Our findings provide promising insights into lncRNAs associated with CAFs in PAAD and provide a personalized tool for predicting patient prognosis and immune microenvironmental landscape.

Abstract 5762: Genomic correlates of response to immune checkpoint blockade in Epstein-Barr virus-associated pulmonary lymphoepithelioma-like carcinoma

Abstract Introduction: Pulmonary lymphoepithelioma-like carcinoma (PLELC) is a rare and distinct subtype of non-small cell lung cancer (NSCLC). The use of immune checkpoint inhibitors (ICIs) for advanced PLELC and tumor genomic features underlying varied treatment responses remains poorly investigated. Methods: The study involved 33 PLELC patients with clinically annotated outcomes to ICIs. Targeted sequencing covering 520 cancer related genes were performed in 22 patients to identify single nucleotide variations (SNVs), copy number variations (CNVs), tumor mutation burden (TMB) and microsatellite instability. Mutation profiles of PLELC were compared with other NSCLC subtypes including lung adenocarcinoma (LUAD) and squamous cell lung carcinoma (LUSC) as well as EBV (Epstein-Barr virus) positive nasopharyngeal carcinoma (NPC) in public databases. Associations between PLELC mutation profiles and treatment responses to ICIs were analyzed. An external dataset of ICI-treated melanoma was used in further analysis of B2M. Results: The objective response rate (ORR), disease control rate (DCR), durable clinical benefit (DCB) rate, and median PFS was 18.2%, 60.6%, 45.5%, and 4.5 months respectively. Genetic alterations were frequently identified in B2M (9 of 22, 41%), CDKN1B (7 of 22, 32%), TP53 (6 of 22, 27%), SGK1 (5 of 22, 23%), NFKBIA (4 of 22, 18%) and TNFAIP3 (4 of 22, 18%). CNVs were comprehensively presented in PLELC while SVNs were less common. In our study, 8 of 9 tumors with B2M mutations and all tumors with CDKN1B, SGK1, TNFAIP3 mutations harbored copy number amplifications. Mutation profiles of PLELC were largely different from those of LUAD and LUSC but were similar to NPC. The median TMB was 2.99 mutations/Mb. All tumors were microsatellite stable (MSS). Patients with higher TMB showed improved DCR (p=0.029), PFS (p=0.056) and overall survival (p=0.038) than those with lower TMB. Patients with lower baseline plasma EBV DNA level also had longer PFS (p<0.001). The presence of B2M amplifications was significant associated with higher TMB level (p=0.022). The PFS of 7 patients with high TMB and amplified B2M were significantly longer than that of other patients (p=0.046). In the external dataset, higher expression of B2M was associated with better ICI responses for melanoma (p<0.05). Pathways involving anti-tumor immune responses such as NK cell-mediated cytotoxicity, antigen processing and presentation were correlated with high B2M expression while Wnt, TGF-beta and MAPK pathways that define poor response to ICI were correlated with low B2M expression. Conclusion: Our study observed comprehensive CNVs in PLELC patients which is a unique molecular feature compared with other NSCLC subtypes and EBV-positive NPC. Higher TMB level and amplifications of B2M in PLELC patients may be used as potential biomarkers to indicate better treatment responses to ICIs. Citation Format: Li-na He, Xuanye Zhang, Xinze Lv, Yuxi Zhou, Min Li, Ting Hou, Wenjie Sun, Li Zhang, ShaoDong Hong. Genomic correlates of response to immune checkpoint blockade in Epstein-Barr virus-associated pulmonary lymphoepithelioma-like carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5762.

Abstract 5094: A pan-cancer analysis of GRIN2A as a potential biomarker for immune checkpoint therapy

Abstract Background: GRIN2A is the encoding gene of GluN2A, which is a subunit of the N-methyl-D-aspartate receptor, and participates in the regulation of excitatory neurotransmission in the brain. GRIN2A is one of the key genes in epilepsy researches, however, only a few researches have been done on GRIN2A in cancer field. The existing studies showed that GRIN2A mutation was frequently found in melanoma and caused abnormal tumor suppressor function. Besides, GRIN2A mutation was associated with higher tumor mutation burden (TMB) in non-small-cell lung cancer, suggesting that GRIN2A-altered tumors might be more sensitive to immune checkpoint inhibitors (ICIs), but the correlation of GRIN2A mutation status with immune response in clinical remains unknown. Methods: Next generation sequencing (NGS) and clinical data of pan-cancer patients were obtained from two MSK-IMPACT Clinical Sequencing cohorts (MSK-2017, N=10336; MSK-2019, N=1661). The MSK-2019 cohort, which was treated with ICIs, were analyzed to explore the association between GRIN2A alteration and therapeutic efficacy of ICIs. Moreover, mRNA expression data of 10201 pan-cancer patients were obtained from the Cancer Genome Atlas (TCGA) database to explore the association between GRIN2A expression level and immune cell infiltration. Results: In total, 3.74% (387/10336) of pan-cancer patients in MSK-2017, and 7.47% (124/1661) in MSK-2019, carried GRIN2A alteration. In MSK-2017, the top three GRIN2A alteration frequency cancer types were melanoma (68/365, 18.63%), skin cancer (non-melanoma, 22/148, 14.86%) and small cell lung cancer (11/82, 13.41%), respectively. And the commonly mutation types of GRIN2A were missense mutation. In MSK-2019 treated with ICIs, the TMB level of GRIN2A-altered group was significantly higher than wild group (median TMB, altered-type vs. wild-type = 25.09 vs. 5.90 Muts/Mb, P<0.0001) and the overall survival (OS) of GRIN2A-altered group were significantly longer than wild group (OS, median, 44.00 vs. 15.00 months; HR=0.5812 [95%CI: 0,4474-0.7550], P=0.0008). But in MSK-2017 without immunotherapy, there was no difference in OS between GRIN2A-altered group and wild group (OS, median, 26.00 vs. 26.13 months; HR=1.194 [95%CI: 0.9588-1.487], P=0.0849). Furthermore, the GRIN2A expression level was positively correlated with the degree of immune cell infiltration in some tumor types, such as prostate adenocarcinoma (PRAD), while some tumors did the opposite, such as sarcoma (SARC). Conclusion: The results indicated that GRIN2A gene alteration was associated with a higher TMB level in pan-cancer patients, and patients carrying GRIN2A alteration might easily benefit from ICIs. Citation Format: Mei Jiang, Xuefeng Zhong, Mengli Huang. A pan-cancer analysis of GRIN2A as a potential biomarker for immune checkpoint therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5094.

Abstract 5102: Correlation analysis of CREBBP mutation with tumor mutation burden and effect of immune checkpoint therapy in bladder cancer

Abstract Background: CREB-binding protein (CREBBP, hereafter CBP) encoded the protein having intrinsic histone acetyltransferase activity, which stabilized the additional protein interactions with the transcription complex. The mutation of CREBBP has been reported that caused Rubinstein-Taybi syndrome (RTS) and associated with acute myeloid leukemia, but not been studied in bladder cancer (BLCA). Immune checkpoint therapy (ICI) has significantly became one of the primary treatment of BLCA, and Tumor mutation burden (TMB) has been regarded as the most prevalent biomarker to predict immunotherapy. The CREBBP mutation status correlation with TMB and immune response remain unknown. Methods: Whole exome sequencing (WES) data and clinical data of 406 BLCA patients was obtained from the Cancer Genome Altas (TCGA). The mutation data of 206 FFPE tumor samples from Chinese BLCA patients were sequenced by targeted next-generation sequencing (NGS, 3DMed panel). NGS data and clinical data of 192 advanced BLCA patients treated with ICI were obtained from the MSK-IMPACT Clinical Sequencing cohort (MSKCC). The association between CREBBP mutation and TMB level in BLCA were explored. Survival analysis was determined by Kaplan-Meier (KM) analysis. Results: In total, The CREBBP mutation frequency was 16.25% (66/406) of BLCA patients in TCGA, 14.56% (30/206) in Chinese cohort and 13.54 (26/192). In Chinese cohort, the alteration frequency of NOTCH signal pathways affected was 48.54% (100/206), in which the highest frequency genes was CREBBP. The TMB level in CREBBP mutant group was higher than wild-type group both in Chinese group (Wilcoxon test, p = 0.001) and MSKCC cohort (Wilcoxon test, p < 0.001). The survival analysis were performed on patients from TCGA cohorts without treatment information and MSKCC BLCA patients treated with ICIs, separately. In TCGA cohort, there are not significantly difference between CREBBP mutation group (n=65) and wild-type group (n=340). While in MSKCC ICIs treatment cohort, the overall survival (OS) of CREBBP mutation group (n=26) were significantly longer than wild-type group (n=166) (median OS, mutation vs wild-type = NE vs 15 months; HR 0.468 [95% CI 0.26-0.84]; P = 0.0431). Conclusion: The CREBBP gene mutation was associated with higher TMB level. Clinical cohort analysis results suggested that CREBBP might be a predictive biomarker of immune checkpoint therapy but not a prognostic factor in BLCA. Citation Format: Abai Xu, Tingting Chen. Correlation analysis of CREBBP mutation with tumor mutation burden and effect of immune checkpoint therapy in bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5102.

The clinical implications of TMB and the relationship between TMB and EGFR mutations in non-small cell lung cancer of Xuanwei, China.

e20512 Background: Xuanwei lung cancer is a type of non-small cell lung cancer that occurs in Xuanwei, southwest China. It is different from non-Xuanwei non-small cell lung cancer in many aspects. The key is that Xuanwei lung cancer does not currently have a recognized prognostic biomarker. The significant molecular difference between Xuanwei lung cancer and non-Xuanwei lung cancer is the mutation type and mutation ratio of EGFR. Are different mutations of EGFR related to the prognosis of Xuanwei lung cancer? What are the reasons for the difference between Xuanwei lung cancer and non-Xuanwei lung cancer? These are clinical issues that we are very interested in. In addition, tumor mutation burden (TMB) has been shown to be an effective biomarker for predicting the clinical outcome of multiple cancer types. However, its prognostic value in Xuanwei lung cancer remains unknown. Methods: The Formalin-Fixed Paraffin-Embedded (FFPE) tissues samples from 172 primary NSCLC patients who have underwent next-generation sequencing (NGS) in a laboratory accredited by the College of American Pathologists (CAP) and Clinical Laboratory Improvement Amendment (CLIA) (3D Medicines Inc., Shanghai, China) from June 2015 to October 2020 were analyzed. The written informed consent was obtained from all included patients. The postoperative follow-up data of all these NSCLC patients were collected. Results: The prognosis of Xuanwei lung cancer is better than that of non-Xuanwei (p < 0.05). Xuanwei is superior to non-Xuanwei mainly in EGFR-positive patients (p < 0.05). Among patients without EGFR mutations, there is no difference in the prognosis of Xuanwei lung cancer and non-Xuanwei lung cancer. Further analysis revealed that there is a difference in TMB levels between Xuanwei lung cancer and non-Xuanwei lung cancer. The TMB level in Xuanwei lung cancer is significantly higher than that in non-Xuanwei lung cancer (p < 0.05). EGFR mutations can be used as prognostic markers for Xuanwei lung cancer, and this is related to patients with EGFR mutations having higher TMB levels. Our research results indicate that EGFR mutation may help combine traditional clinicopathological risk factors to optimize risk stratification and guide treatment decisions. Conclusions: Xuanwei lung cancer is a special subtype of NSCLC with different molecular features and prognosis. Analysis of data in this area will lead to the development of precision treatment options for Xuanwei lung cancer.

Comprehensive molecular characterization of Chinese patients with biliary tract cancers.

e16153 Background: Biliary tract cancers are clinically heterogenous with poor prognosis. The traditional location-based classification of biliary tract cancers is helpful while the boundary between subtypes is still ambiguous. We hereby analyzed the comprehensive molecular characterizations across different types among biliary tract cancers and further to identify the similarities and differences and help with the individualized treatment. Methods: Tumor tissue samples from 219 Chinese biliary tract cancer patients were profiled by next generation sequencing with a 539 gene panel by the Illumina NovaSeq 6000 (Illumina, San Diego, CA, USA) sequencing platform. Tumor mutation burden (TMB) was calculated by counting all nonsynonymous mutations per megabase of coding sequences. Results: A total of 219 biliary tract cancer (BTC) patients with a median age of 61 years(range 29–83 years) were enrolled, including 147 gallbladder cancer (GBC), 51 intrahepatic cholangiocarcinoma (iCCA) and 21 hilar cholangiocarcinoma (hCCA). These samples consisted of 93 males and 126 females. The most frequent mutated genes were TP53 (73%), ARID1A (18%), MUC16 (16%) in GBC, TP53 (57%), KRAS (35%), ARID1A (16%), PIK3CA (16%) in iCCA, TP53 (48%), KRAS (29%), ARID1A (14%) in hCCA. The mutation of BCORL1 (P = 0.002) and IRF4 (P = 0.006) had a significant association with age. The median TMB was 4.26 mutations/Mb in GBC, 2.94 mutations/Mb in iCCA and 2.84 mutations/Mb in hCCA. Patients with ATM mutation and FAT1 mutation had a significant higher TMB level (P＜0.001). The mutations of common target genes in different types of BTC were analyzed. The mutations of IDH1, target gene of Ivosidenib, were detected in 4 (1.83%) patients (1 in GBC, 2 in iCCA, 1in hCCA). The mutations of FGFR1/2/3/4, target gene of Erdafitinib, were detected in 10 (4.57%) patients (8 in GBC, 2 in iCCA, 0 in hCCA). The most frequently affected pathways in GBC, iCCA and hCCA were TP53 (78.2%, 60.8%, 47.6%), RTK-RAS (52.4%, 64.7%, 47.6%), PIK3 (34%, 39.2%, 33.3%). Conclusions: The genomic profiling and molecular characterization among different anatomic locations could support the exploration of tumor development mechanism and provide theoretic basis for developing diagnosis and treatment methods for biliary tract cancers patients.

An Immune-Related lncRNA Signature to Predict the Biochemical Recurrence and Immune Landscape in Prostate Cancer.

PurposeThis study aims to construct an immune-related signature to provide comprehensive insights into the immune landscape of prostate cancer, which can predict biochemical recurrence (BCR) and clinical treatment.MethodsBased on The Cancer Genome Atlas (TCGA) dataset, a signature constructed by DEirlncRNAs pairs was determined. The receiver operating characteristic curve analysis, Kaplan–Meier analysis, nomogram, and decision curve analysis were used to analyze it. Then, immunophenoscore (IPS), immune cell infiltration, tumor mutation burden (TMB), and immune function were investigated. Finally, we evaluated the role of the signature in medical treatment.ResultsA signature constructed by 10 valid DEirlncRNAs pairs was identified in the training set and validated well in the testing and entire set. The signature was a reliable and independent prognostic indicator to predict the BCR of prostate cancer, which was better than the clinicopathological characteristics. After dividing the patients into low- and high-risk groups by median value, we found that the high-risk group had shorter BCR-free time and higher TMB levels. Furthermore, the high-risk group was negatively associated with plasma B cells and CD+8 T cells. IPS and immune functions, such as immune checkpoints and human leukocyte antigen, were significantly different between the two groups. Low-risk group was more sensitive to endocrine therapy and immunotherapy, while high-risk group was more inclined to targeted drugs. Both groups had their own sensitive chemotherapy.ConclusionWe established a novel signature to predict BCR and validated its role in the immune landscape of prostate cancer, which could help patients receive personalized medical treatment.

The prevalence of HLA-I LOH in Chinese pan-cancer patients and genomic features of patients harboring HLA-I LOH.

HLA-I LOH may facilitate immune evasion. However, large population studies on the prevalence of HLA-I LOH across different cancer types and in relation to mutational profiles are lacking, in particular, in the Chinese population. In this study, analysis was performed in 1504 advanced pan-cancer patients and 134 early-stage non-small-cell lung cancer patients using a 1021-gene panel. The consistency between the 1021-gene panel and whole-exome sequencing was evaluated in 45 samples, where concordant results were obtained in 95.6% (43/45) of the samples. Analytical results revealed that the prevalence of HLA-I LOH in tumor tissue presents considerable differences across cancer types. HLA-I LOH was relevant to genomic instability, reflected in higher tumor mutation burden level. HLA-I LOH occurs more frequently in MSS samples than in MSI-H samples. The alteration frequencies of p53 pathway, RTK/RAS pathway, Notch pathway, Hippo pathway, and Nrf2 pathway in HLA-I LOH group were significantly higher than that in HLA-I stable group (p < .0001, p < .0001, p = .032, p = .013, p = .003, respectively). In DNA damage response pathways, alterations in the checkpoint factor pathway and Fanconi anemia pathway are enriched in HLA-I LOH group (p < .0001, p = .023, respectively). Besides, HLA-I LOH was accompanied by higher mutation rates of several tumor suppressors, including TP53 and LRP1B. These results may shed light on follow-up tumor immunology research.