High TMB Research Articles

A novel somatic mutation in POLE exonuclease domain associated with ultra-mutational signature and MMR deficiency in endometrial cancer: a case report

BackgroundDefect in proofreading exonuclease activity of polymerases epsilon and delta (Pols ε and δ) leads to mutagenesis and genomic instability and has been described in several cancer types. Somatic POLE exonuclease domain mutations (EDMs) have been reported in 7–12% endometrial cancers (ECs) and defined a subgroup of endometrial cancers with ultrahigh somatic mutation frequencies, high tumor infiltrated lymphocytes and favorable outcomes.Case presentationHerein, we presented a novel somatic mutation in POLE exonuclease domain associated with ultra-mutational signature and MMR deficiency in endometrial cancer. A novel POLE EDM (p.T278K) was found by a 11-gene NGS panel. The MSS status detected by the MSI test was inconsistent with the dMMR status by IHC. The loss of MSH6 expression in the tumor could be interpreted by the two nonsense mutations (p.E1234* and p.E1322*) of the MSH6 gene which may lead to truncated proteins. The T278K mutation was pathogenic identified by a 602-gene NGS panel with 27.3% of C > A substitution, 0.6% of indels, 0.6% of C > G substitution and a high TMB of 203.8 mut/Mb.ConclusionsWe report an endometrial cancer patient harbored a novel somatic POLE T278K mutation. This mutation was a novel pathogenic POLE EDM should be considered as “POLE (ultramutated)” in clinical practice for the molecular classification of EC.

Emerging glyco-risk prediction model to forecast response to immune checkpoint inhibitors in colorectal cancer.

Aberrant glycosylation is one of the most common post-translational modifications leading to heterogeneity in colorectal cancer (CRC). This study aims to construct a risk prediction model based on glycosyltransferase to forecast the response to immune checkpoint inhibitors in CRC patients. Based on the TCGA dataset and glycosyltransferase genes, the NMF algorithm and WGCNA were used to identify molecular subtypes and co-expressed genes, respectively. Lasso and multivariate COX regression were used to identify prognostic glycosyltransferase genes and construct a glyco-risk prediction model in CRC patients. Univariate and multivariate Cox regression, Kaplan-Meier, and ROC curves were applied to further verify the prognostic performance of the model in CRC patients in the training and validation sets. We compared the responsiveness of immunotherapy and chemotherapy between the two groups. In vitro experiments and clinical specimens verified the specific function of the key glycosyltransferase genes in CRC. The CRC cohort was divided into two subtypes with prominent differences in survival based on the well-robust seven-gene glyco-risk prediction model (composed of ALG1L2, HAS1, PYGL, COLGALT2, B3GNT4, POFUT2, and GALNT7). The nomograms based on the risk model could predict the prognosis of CRC patients independently of other clinicopathologic characteristics. Our prediction model showed a better overall prediction performance than other models. Compared with the low-risk group, the high-risk CRC patients showed a lower immune infiltration state, but a higher TMB and a lower response to anti-PD-1, anti-PD-L1, and anti-CTLA-4 therapy. Clinical specimen validation showed an obvious difference in the expression of seven glycosyltransferase genes between the low- and high-risk groups. Significant reduction in POFUT2 expression in high-risk groups was associated with reduced N-glycans production. Our study constructed a robust glyco-risk prediction model that could provide direction for immunotherapy and chemotherapy in CRC patients, which could help clinicians make personalized treatment decisions.

Tissue factor expression in colorectal cancer.

250 Background: Tissue factor (TF), a component of the coagulation cascade, transmembrane receptor, and cofactor for factor VII/VIIa is expressed by subendothelial cells and critical to hemostasis, thrombosis, cell proliferation, angiogenesis, and metastasis. TF is suggested to have a critical role in colorectal cancer (CRC). Here we assessed the clinico-molecular features associated with TF expression (exp) in CRC. Methods: Tumor molecular profiling was performed for 14,0786 samples by NextGen Sequencing on DNA (592 genes or WES) and RNA (WTS) and immunohistochemistry (IHC) at Caris Life Sciences (Phoenix, AZ). TF-high (TF-H) and TF-low (TF-L) RNA exp were defined as ≥ 75th- and < 25th-percetile of TF transcripts per million (TPM), respectively. X2/Fisher-exact and Mann Whitney U tests were used for comparison, and P-values were adjusted for multiple comparisons. Cell infiltration in the tumor microenvironment (TME) was estimated by quanTIseq. Real-world overall survival (OS) information was obtained from insurance claims data and Kaplan-Meier estimates were calculated for molecularly defined patients (pts). Results: TF exp was higher in primary tumors compared to metastatic sites (2.3-fold, P < 0.001); higher in lung vs. liver metastases (0.6-fold and 0.3-fold, p < 0.001); higher in rectal (1.4-fold), right-sided (1.3-fold), and transverse (1.2-fold) compared to left-sided (P < 0.001); and highest in CMS1 tumors (CMS2 0.4-fold, CMS3 0.7-fold, CMS4 0.8-fold, P < 0.001). TF exp was higher in tumors with high TMB (TMB ≥ 10 Mut/Mb) (1.6-fold), dMMR/MSI-H (1.9-fold), and PD-L1 exp (1.8-fold) (P < 0.001 each). Compared to WT tumors, mutations in KRAS (1.2-fold, P < 0.001), BRAF (1.5-fold, P < 0.001) and ERBB2 (1.2-fold, P < 0.01) were associated with higher TF exp. In pMMR/MSS CRC, TF-L tumors were associated with TP53, APC, and NRAS mutations, and TF-H was associated with KRAS, PIK3CA, SMAD4, FBXW7, BRAF, ARID1A, GNAS, SMAD2, RNF43, KMT2D and BRCA1 mutations. TF exp was positively associated with most immune cell populations, most strongly with endothelial cells. In pMMR/MSS KRAS WT CRC, TF-H was associated with worse OS than TF-L. TF-H was also associated with worse OS for pMMR/MSS CRC pts treated with FOLFOX (HR: 1.5, CI:1.2-1.8, p < 0.0001), FOLFIRI (HR:1.7, CI:1.3-2.1, p < 0.0001), VEGF (HR:1.3, CI:1.1-1.6, p = 0.002) and EGFR inhibitors (HR:1.6, CI:1.1-2.3, p = 0.009) than TF-L. TF-H was associated with greater median days on pembrolizumab compared to TF-L in dMMR/MSI-H CRC (HR: 0.6, CI: 0.4-0.9, p = 0.018). Conclusions: Our data show TF exp is associated with distinct clinical and molecular features, including tumor sidedness and metastatic pattern, as well as CMS subtype and KRAS, BRAF and ERBB2 mutations. TME cell infiltration and IO-related biomarkers were enriched in TF-H, with TF exp correlating with endothelial cell abundance. These findings and associations with patient outcomes suggest that TF may be a relevant biomarker and target in CRC.

Prognosis and Personalized Treatment Prediction in Different Mutation-Signature Hepatocellular Carcinoma.

Mutation patterns have been extensively explored to decipher the etiologies of hepatocellular carcinoma (HCC). However, the study and potential clinical role of mutation patterns to stratify high-risk patients and optimize precision therapeutic strategies remain elusive in HCC. Using exon-sequencing data in public (n=362) and in-house (n=30) cohorts, mutation signatures were extracted to decipher relationships with the etiology and prognosis in HCC. The proteomics (n=159) and cell-line transcriptome data (n=1019) were collected to screen the implication of sensitive drugs. A novel multi-step machine-learning framework was then performed to construct a classification predictor, including recognizing stable reversed gene pairs, establishing a robust prediction model, and validating the robustness of the predictor in five independent cohorts (n=900). Two heterogeneous mutation signature clusters were identified, and a high-risk prognosis cluster was recognized for further analysis. Notably, mutation signature cluster 1 (MSC1) was featured by activated anti-tumor immune and metabolism dysfunctional states, higher genomic instability (high TMB, SNV neoantigen, indel neoantigens, and total neoantigens), and a dismal prognosis. Notably, MSC performed as an independent risk factor than clinical traits (eg, stage, vascular invasion). Additionally, afatinib and canertinib were recognized which might have potential therapeutic implications in MSC1, and the targets of these drugs presented a higher expression in both gene and protein levels in HCC. Our studies may provide a promising platform for improving prognosis and tailoring therapy in HCC.

A Novel Prognostic Pyroptosis-Related Gene Signature Correlates to Oxidative Stress and Immune-Related Features in Gliomas.

Gliomas are highly invasive and aggressive tumors having the highest incidence rate of brain cancer. Identifying effective prognostic and potential therapeutic targets is necessitated. The relationship of pyroptosis, a form of programmed cellular death, with gliomas remains elusive. We constructed and validated a prognostic model for gliomas using pyroptosis-related genes. Differentially expressed pyroptosis-related genes were screened using the "limma" package. Based on LASSO-Cox regression, nine significant genes including CASP1, CASP3, CASP6, IL32, MKI67, MYD88, PRTN3, NOS1, and VIM were employed to construct a prognostic model in the TCGA cohort; the results were validated in the CGGA cohort. According to the median risk score, the patients were classified into two risk groups, namely, high- and low-risk groups. Patients at high risk had worse prognoses relative to those at low risk evidenced by the Kaplan-Meier curve analysis. The two groups exhibited differences in immune cell infiltration and TMB scores, with high immune checkpoint levels, TMB scores, and immune cell infiltration levels in the high-risk group. KEGG and GO analyses suggested enrichment in immune-related pathways. Furthermore, we found that the genes in our signature strongly correlated with oxidative stress-related pathways and the subgroups exhibited different ssGSEA scores. Some small molecules targeted the genes in the model, and we verified their drug sensitivities between the risk groups. The scRNA-seq dataset, GSE138794, was processed using the "Seurat" package to assess the level of risk gene expression in specific cell types. Finally, the MYD88 level was lowered in the U87 glioma cell line using si-RNA constructs. Cellular proliferation was impaired, and fewer pyroptosis-related cytokines were released upon exposure to LPS. In summary, we built a pyroptosis-related gene model that accurately classified glioma patients into high- and low-risk groups. The findings suggest that the signature may be an effective prognostic predictive tool for gliomas.

Dramatic response of a negative PD-L1 expression and TMB low pulmonary sarcomatoid carcinoma to sintilimab combined with anlotinib

Pulmonary Sarcomatoid Carcinoma (PSC) is a rare and highly malignant subtype of Non Small Cell Lung Cancer (NSCLC). In contrast to other types of lung cancers, recent retrospective studies demonstrated that PSC always shows frequent genetic mutations, high TMB and high PD L1 expression which indicates these patients might derive survival benefits from immune checkpoint inhibitors

Cuproptosis-associated genes and immune microenvironment characterization in breast cancer

Excess Cu can cause cell death as a cofactor for essential enzymes. The relationship between cuproptosis-associated genes (CAGs) and breast cancer (BR) is not completely investigated. Here, the transcriptome expression and mutation profile data of BR samples from the Cancer Genome Atlas database were retrieved to identify CAGs. Patients with BR were clustered using consensus clustering. A least absolute shrinkage and selection operator analysis was then performed to construct a CAGs risk signature. As a result, all 13 cuproptosis regulators were significantly differentially expressed between BR and normal samples; among them, 9 cuproptosis genes were correlated with prognoses. Patients with BR were separated into 2 clusters that were associated with patient survival, clinical phenotypes, and immune infiltration, Based on the components of cuproptosis. Subsequently, genes differentially expressed between clusters were obtained, and 11 CAGs were ultimately incorporated into the risk signature. Functional analyses revealed that the risk signature correlated with patient outcomes, ER, PR, HER2 expression, and BR IHC subtypes. Additionally, immune microenvironment analyses showed that CAGs-high-risk patients exhibited lower immune cell infiltration and immune functions. Furthermore, high-risk BR patients had higher TMB, lower immune checkpoint expression, higher m6A gene expression, and higher tumor stemness. Finally, the immunophenoscore analysis revealed that the risk signature could potentially predict the immune response in BR and help guide the application of various immunotherapeutic drugs. Overall, the newly constructed CAGs risk signature presented a predictive value for the prognosis and tumor microenvironment of BR patients and can be further used in the guidance of immunotherapy for BR.

Identification and Validation of Cuproptosis-Related LncRNA Signatures in the Prognosis and Immunotherapy of Clear Cell Renal Cell Carcinoma Using Machine Learning.

(1) Objective: We aimed to mine cuproptosis-related LncRNAs with prognostic value and construct a corresponding prognostic model using machine learning. External validation of the model was performed in the ICGC database and in multiple renal cancer cell lines via qPCR. (2) Methods: TCGA and ICGC cohorts related to renal clear cell carcinoma were included. GO and KEGG analyses were conducted to determine the biological significance of differentially expressed cuproptosis-related LncRNAs (CRLRs). Machine learning (LASSO), Kaplan-Meier, and Cox analyses were conducted to determine the prognostic genes. The tumor microenvironment and tumor mutation load were further studied. TIDE and IC50 were used to evaluate the response to immunotherapy, a risk model of LncRNAs related to the cuproptosis genes was established, and the ability of this model was verified in an external independent ICGC cohort. LncRNAs were identified in normal HK-2 cells and verified in four renal cell lines via qPCR. (3) Results: We obtained 280 CRLRs and identified 66 LncRNAs included in the TCGA-KIRC cohort. Then, three hub LncRNAs (AC026401.3, FOXD2-AS1, and LASTR), which were over-expressed in the four ccRCC cell lines compared with the human renal cortex proximal tubule epithelial cell line HK-2, were identified. In the ICGC database, the expression of FOXD2-AS1 and LASTR was consistent with the qPCR and TCGA-KIRC. The results also indicated that patients with low-risk ccRCC-stratified by tumor-node metastasis stage, sex, and tumor grade-had significantly better overall survival than those with high-risk ccRCC. The predictive algorithm showed that, according to the three CRLR models, the low-risk group was more sensitive to nine target drugs (A.443654, A.770041, ABT.888, AG.014699, AMG.706, ATRA, AP.24534, axitinib, and AZ628), based on the estimated half-maximal inhibitory concentrations. In contrast, the high-risk group was more sensitive to ABT.263 and AKT inhibitors VIII and AS601245. Using the CRLR models, the correlation between the tumor immune microenvironment and cancer immunotherapy response revealed that high-risk patients are more likely to respond to immunotherapy than low-risk patients. In terms of immune marker levels, there were significant differences between the high- and low-risk groups. A high TMB score in the high-risk CRLR group was associated with worse survival, which could be a prognostic factor for KIRC. (4) Conclusions: This study elucidates the core cuproptosis-related LncRNAs, FOXD2-AS1, AC026401.3, and LASTR, in terms of potential predictive value, immunotherapeutic strategy, and outcome of ccRCC.

Construction and validation of a novel cuproptosis-related long noncoding RNA signature for predicting the outcome of prostate cancer.

Background: Prostate cancer (PCa) is one of the most common tumors of the urinary system. Cuproptosis is a novel mode of controlled cell death that is related to the development of various tumor types. However, the functions of cuproptosis-related long noncoding RNAs (CRLs) in PCa have not yet been well studied. Methods: In this study, data of PCa patients were obtained from The Cancer Genome Atlas (TCGA) and from the Changhai Hospital. Univariate and multivariate Cox regression analyses and LASSO regression analysis were conducted to screen CRLs linked to the prognosis of PCa patients. A risk score model was constructed on the basis of CRLs to predict prognosis. PCa patients were categorized into high- and low-risk cohorts. The predictive value of the risk score was evaluated by Kaplan-Meier survival analysis, receiver operating characteristic curves, and nomograms. In addition, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to explore possible pathways involving CRLs in PCa. Immune function analysis confirmed the correlation between CRLs and immunity in PCa. Finally, we explored the tumor mutational burden and drug response in the high- and low-risk cohorts. Results: First, we identified seven CRLs (C1orf229, C9orf139, LIPE-AS1, MCPH1-AS1, PRR26, SGMS1-AS1, and SNHG1) that were closely related to prognosis in PCa. The risk score model based on the selected CRLs could accurately predict the prognosis of PCa patients. The high-risk cohort was associated with worse disease-free survival (DFS) time in PCa patients (p < 0.001). ROC curve analysis was performed to confirm the validity of the signature (area under the curve (AUC) at 1year: 0.703). Nomograms were constructed based on the risk score and clinicopathological features and also exhibited great predictive efficiency for PCa. GO and KEGG analyses showed that the CRLs were mainly enriched in metabolism-related biological pathways in PCa. In addition, immune function analysis showed that patients in the high-risk cohort had higher TMB and were more sensitive to conventional chemotherapy and targeted drugs including doxorubicin, epothilone B, etoposide, and mitomycin C. Conclusion: We constructed a novel CRL-related risk score model to accurately predict the prognosis of PCa patients. Our results indicate that CRLs are potential targets for drug therapy in PCa and provide a possible new direction for personalized treatment of PCa patients.

Non‑small cell lung cancer carrying PBRM1 mutation suggests an immunologically cold phenotype leading to immunotherapy failure even with high TMB

High tumor mutation load (TMB-H, or TMB ≥ 10) has been approved by the U.S. FDA as a biomarker for pembrolizumab treatment of solid tumors, including non‑small cell lung cancer (NSCLC). Patients with cancer who have immunotherapy-resistant gene mutations cannot achieve clinical benefits even in TMB-H. In this study, we aimed to identify gene mutations associated with immunotherapy resistance and further informed mechanisms in NSCLC. A combined cohort of 350 immune checkpoint blockade-treated patients from Memorial Sloan Kettering Cancer Center (MSKCC) was used to identify genes whose mutations could negatively influence immunotherapy efficacy. An external NSCLC cohort for which profession-free survival (PFS) data were available was used for independent validation. CIBERSORT algorithms were used to characterize tumor immune infiltrating patterns. Immunogenomic features were analysed in the TCGA NSCLC cohort. We observed that PBRM1 mutations independently and negatively influence immunotherapy efficacy. Survival analysis showed that the overall survival (OS) and PFS of patients with PBRM1 mutations (MT) were significantly shorter than the wild type (WT). Moreover, compared with PBRM1-WT/TMB-H group, OS was worse in the PBRM1-MT/TMB-H group. Notably, in patients with TMB-H/PBRM1-MT, it was equal to that in the low-TMB group. The CIBERSORT algorithm further confirmed that the immune infiltration abundance of CD8+ T cells and activated CD4+ memory T was significantly lower in the MT group. Immunogenomic differences were observed in terms of immune signatures, T-cell receptor repertoire, and immune-related genes between WT and MT groups. Nevertheless, we noticed an inverse relationship, given that MT tumors had a higher TMB than the WT group in MSKCC and TCGA cohort. In conclusion, our study revealed that NSCLC with PBRM1 mutation might be an immunologically cold phenotype and exhibited immunotherapy resistance. NSCLC with PBRM1 mutation might be misclassified as immunoresponsive based on TMB.

T cells of colorectal cancer patients’ stimulated by neoantigenic and cryptic peptides better recognize autologous tumor cells

BackgroundPatients with cancers that exhibit extraordinarily high somatic mutation numbers are ideal candidates for immunotherapy and enable identifying tumor-specific peptides through stimulation of tumor-reactive T cells (Tc).MethodsColorectal cancers (CRC) HROC113...

Efficacy and safety of immune checkpoint inhibitors in advanced pancreatic cancer: A real world study in Chinese cohort

ABSTRACT Previous clinical studies had not shown expected results in advanced pancreatic cancer (APC) with single-agent checkpoint inhibitors. Until the present day, little is known about their performance in real-world settings. So, in this study, we investigate the ICIs’ efficacy and safety in Chinese APC patients. Patients with APC who received ICIs between November 2018 to June 2021 were enrolled in this retrospective study. The efficacy end points included overall survival (OS), progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR) and adverse events (AEs). This study included 104 patients and the median OS (mOS) and median PFS (mPFS) were 9.1 and 5.4 months, respectively. In the subgroup analyses, the mOS was longer for patients receiving combined radiotherapy than for those that didn’t (13.8 vs 7.0 months, p < .001), whereas the mPFS was also longer, and the ORR and DCR were higher. Specifically, the mOS was longer for patients who had received a combination of chemotherapy than for those combined with targeted therapy (11.6 vs 5.6 months, p = .002), with the mPFS being also longer. ICIs as a first-line treatment could resulted to better survival. The mOS was longer for patients with a high TMB compared to those with low (19.3 vs 7.2 months, p = .004), whereas AEs were considered to be tolerable. The combination therapy of ICIs was proved to be safe and effective for treating APC, especially the combination of chemotherapy and radiotherapy, which would benefit from additional prospective studies.

Genomic Landscape and Distinct Molecular Subsets of Primary Testicular Lymphoma

Primary testicular lymphoma (PTL) is a malignant aggressive tumor that occurs in older men, and which is 90% histologically diffuse large B-cell lymphoma (PT-DLBCL). However, as a malignant tumor occurring in an immune privileged site, it is not very effective against a wide range of treatments and its prognosis is not satisfactory. To gain insight into the pathogenesis of PTL and the factors associated with its poor prognosis, the whole-exome sequencing analysis of 25 PTL patients were performed. Single-nucleotide variation (SNV) were analyzed through GATK and ANNOVAR workflows. In summary, we identified a number of high-frequency mutant genes, such as MYD88, HLA-A, PIM1 and so on. These high-frequency mutated genes are compatible with the high-frequency mutated genes that have appeared in previous studies on the genetic characteristics. However, we also identified some high-frequency mutated genes that have been rarely mentioned in previous articles. In addition, we calculated the TMB in order to see if the mutation had any impact on the prognosis and recurrence rate of the patients, and the results showed that a high TMB predicted a low progression-free survival (PFS). Notably, we will further analyze TMB and CNV to differentiate molecular subsets groups of PTL patients, which will have a basis for future immunotherapy in PTL.

Genomic landscape, immune characteristics and prognostic mutation signature of cervical cancer in China

PurposeThis study aimed to analyse the genomic alteration profiles and immune characteristics of a cohort of Chinese cervical cancer patients to understand why certain patients benefited from molecular targeted therapies and immunotherapy as well as their prognostic significance.MethodsPD-L1 expression and clinicopathological information were obtained from 98 cervical cancer patients. Differences in PD-L1 expression and gene mutations between squamous cell carcinoma (SCC) and adenocarcinoma (AC) were analysed by the chi-square test or Fisher's exact test. Differences in gene mutations between our cohort and The Cancer Genome Atlas (TCGA) cohort were tested by Fisher's exact test. Logistic regression was used to analyse factors influencing TMB-high.ResultsPositive PD-L1 expression was significantly higher in cervical SCC than in cervical AC (87% vs. 39%, p < 0.001). Frequently mutated genes in cervical cancer included the PIK3CA, KMT2D, and KMT2C genes, among others. PIK3CA gene mutation rates were significantly higher in SCC than in AC (p = 0.004). The TERT gene mutation rate was significantly higher in our cohort than in the TCGA cohort (12% vs. 1%, p < 0.001). The independent predictors of high TMB were KMT2C and LRP1B gene mutations (p < 0.05). We also found that PTEN mutations were associated with worse survival (median PFS, 12.16 vs. 21.75 months, p = 0.0024).ConclusionCervical SCC and AC have different molecular profiles and immune characteristics, suggesting that targeted treatments for SCC and AC patients may improve clinical outcomes. KMT2C and LRP1B gene mutations are independent predictors of TMB-high status in cervical cancer. We also proposed the prognostic value of PTEN mutations.

Prognostic characteristics of immune subtypes associated with acute myeloid leukemia and their identification in cell subsets based on single-cell sequencing analysis.

Immune genes play an important role in the development and progression of acute myeloid leukemia (AML). However, the role of immune genes in the prognosis and microenvironment of AML remains unclear. In this study, we analyzed 151 AML patients in the TCGA database for relevant immune cell infiltration. AML patients were divided into high and low immune cell infiltration clusters based on ssGSEA results. Immune-related pathways, AML pathways and glucose metabolism pathways were enriched in the high immune cell infiltration cluster. Then we screened the differential immune genes between the two immune cell infiltration clusters. Nine prognostic immune genes were finally identified in the train set by LASSO-Cox regression. We constructed a model in the train set based on the nine prognostic immune genes and validated the predictive capability in the test set. The areas under the ROC curve of the train set and the test set for ROC at 1, 3, 5 years were 0.807, 0.813, 0.815, and 0.731, 0.745, 0.830, respectively. The areas under ROC curve of external validation set in 1, 3, and 5 years were 0.564, 0.619, and 0.614, respectively. People with high risk scores accompanied by high TMB had been detected with the worst prognosis. Single-cell sequencing analysis revealed the expression of prognostic genes in AML cell subsets and pseudo-time analysis described the differentiation trajectory of cell subsets. In conclusion, our results reveal the characteristics of immune microenvironment and cell subsets of AML, while it still needs to be confirmed in larger samples studies. The prognosis model constructed with nine key immune genes can provide a new method to assess the prognosis of AML patients.

Identification of novel cuproptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of breast cancer patients.

BackgroundCuproptosis is a new modality of cell death regulation that is currently considered as a new cancer treatment strategy. Nevertheless, the prognostic predictive value of cuproptosis-related lncRNAs in breast cancer (BC) remains unknown. Using cuproptosis-related lncRNAs, this study aims to predict the immune microenvironment and prognosis of BC patients. and develop new therapeutic strategies that target the disease.MethodsThe Cancer Genome Atlas (TCGA) database provided the RNA-seq data along with the corresponding clinical and prognostic information. Univariate and multivariate Cox regression analyses were performed to acquire lncRNAs associated with cuproptosis to establish predictive features. The Kaplan-Meier method was used to calculate the overall survival rate (OS) in the high-risk and low-risk groups. High risk and low risk gene sets were enriched to explore functional discrepancies among risk teams. The mutation data were analyzed using the “MAFTools” r-package. The ties of predictive characteristics and immune status had been explored by single sample gene set enrichment analysis (ssGSEA). Last, the correlation between predictive features and treatment condition in patients with BC was analyzed. Based on prognostic risk models, we assessed associations between risk subgroups and immune scores and immune checkpoints. In addition, drug responses in at-risk populations were predicted.ResultsWe identified a set of 11 Cuproptosis-Related lncRNAs (GORAB-AS1, AC 079922.2, AL 589765.4, AC 005696.4, Cytor, ZNF 197-AS1, AC 002398.1, AL 451085.3, YTH DF 3-AS1, AC 008771.1, LINC 02446), based on which to construct the risk model. In comparison to the high-risk group, the low-risk patients lived longer (p < 0.001). Moreover, cuproptosis-related lncRNA profiles can independently predict prognosis in BC patients. The AUC values for receiver operating characteristics (ROC) of 1-, 3-, and 5-year risk were 0.849, 0.779, and 0.794, respectively. Patients in the high-risk group had lower OS than those in the low-risk group when they were divided into groups based on various clinicopathological variables. The tumor burden mutations (TMB) correlation analysis showed that high TMB had a worse prognosis than low-TMB, and gene mutations were found to be different in high and low TMB groups, such as PIK3CA (36% versus 32%), SYNE1 (4% versus 6%). Gene enrichment analysis indicated that the differential genes were significantly concentrated in immune-related pathways. The predictive traits were significantly correlated with the immune status of BC patients, according to ssGSEA results. Finally, high-risk patients showed high sensitivity in anti-CD276 immunotherapy and conventional chemotherapeutic drugs such as imatinib, lapatinib, and pazopanib.ConclusionWe successfully constructed of a cuproptosis-related lncRNA signature, which can independently predict the prognosis of BC patients and can be used to estimate OS and clinical treatment outcomes in BRCA patients. It will serve as a foundation for further research into the mechanism of cuproptosis-related lncRNAs in breast cancer, as well as for the development of new markers and therapeutic targets for the disease.

Identifying the EMT-related signature to stratify prognosis and evaluate the tumor microenvironment in lung adenocarcinoma.

Background: Epithelial-mesenchymal transition (EMT) is a critical process in tumor invasion and metastasis. EMT has been shown to significantly influence the invasion, metastasis, and poor prognosis in lung adenocarcinoma (LUAD). This study aimed to develop a novel EMT-related prognostic model capable of predicting overall survival (OS) in patients with LUAD. Methods: A total of 283 LUAD patients from TCGA RNA-seq dataset were assigned to a training cohort for model building, and 310 LUAD patients from GEO RNA-seq dataset were assigned to a validation cohort. EMT genes were acquired from MsigDB database and then prognosis-related EMT genes were identified by univariate Cox regression. Lasso regression was then performed to determine the genes and the corresponding variables to construct a prognosis risk model from the training cohort. Furthermore, characteristics of the tumor microenvironment (TME), mutation status and chemotherapy responses were analyzed to assess the differences between the two risk groups based on the prognostic model. In addition, RT-qPCR was employed to validate the expression patterns of the 6 genes derived from the risk model. Results: A six-gene EMT signature (PMEPA1, LOXL2, PLOD2, MMP14, SPOCK1 and DCN) was successfully constructed and validated. The signature assigned the LUAD patients into high-risk and low-risk groups. In comparison with the low-risk group, patients in the high-risk group had a significantly lower survival rate. ROC curves and calibration curves for the risk model demonstrated reliable stratification and predictive ability. The risk model was robustly correlated with multiple TME characteristics. Besides, the data showed that patients in the low-risk group had more immune activities, higher stemness scores and cytolytic activity scores and higher TMB. In addition, RT-qPCR results revealed that PMEPA1, LOXL2, PLOD2, MMP14, and SPOCK1 were notably upregulated in LUAD tissues, while DCN was downregulated. Conclusion: Our study successfully developed a novel EMT-related signature to predict prognosis of LUAD patients and guide treatment strategies. The six genes derived from the prediction signature might play a potential role in antitumor immunity and serve as promising therapeutic targets in LUAD.

1405P Circulating tumor DNA in advanced prostate cancer: Focus on high blood tumor mutational burden (h-bTMB)

High TMB is a promising predictive biomarker for immune checkpoint blockade. Circulating tumor DNA (ctDNA) from plasma is a minimally invasive method that may ease TMB assessment. Prevalence and characteristics of metastatic prostate cancer (mPC) with high TMB is not well described.

1081P DNA damage response and repair (DDR) gene mutations as an alternative mechanism to generate high TMB in never smoker NSCLC patients

Immune checkpoint inhibitors (IO) single agent or in combination with platinum-based chemotherapy (CT-IO) are standard of care for Stage IV and not oncogene addicted non-small cell lung cancer (aNSCLC) according to PD-L1 expression. The presence of a high tumor mutation burden (H-TMB) is one of the most debated biomarkers for IO response. Smoking-induced harm is a mechanism that generates an H-TMB in aNSCLC smoking patients (S-pts), whereas never-smoking patients (NS-pts) usually have a low TMB and are unresponsive to IO. However, the subgroup of NS-pts with an H-TMB has not yet been well characterized molecularly. We retrospectively collected clinical data from a single-center cohort of 142 aNSCLC pts with PD-L1 ≥ 50% treated with first-line pembrolizumab between January 2017 to March 2021. Next-generation sequencing (NGS) analysis using the FoundationOne®CDx assay (Foundation Medicine, Cambridge, MA, USA) was performed to correlate genetic alterations with clinical characteristics and response outcomes. We classified all detected mutations into eleven main pathways: cell cycle pathway, Hippo pathway, Myc pathway, Notch pathway, Oxidative stress/Nrf2 pathway, PI3K pathway, RTK/RAS/MAP pathway, TGF beta pathway, p53 pathway, beta-catenin/Wnt pathway and DDR pathway. Lastly, we identified the pathways with at least one mutation for each patient and performed enrichment analysis to characterize patients’ subgroups in terms of mutated pathways. With a median follow-up of 22 months (m), mPFS was 9.9 m, and mOS was 10.6 m. There were 111 S-pts and 31 NS-pts. The cohort of S-pts had higher TMB than the NS-pts cohort (TMB average 10.05 vs. 8.86 Mut/Mb). However, a subgroup of 11 NS-pts with high TMB (39-11 Mut/Mb) was identified. This subgroup was particularly enriched in DDR pathway mutations (p-value=0.0016) compared to the rest of the series and the H-TMB/S-pts subgroup. All H-TMB/NS-pts responded to IO treatment with an mPFS of 10.9 m and mOS of 12.7 m. Our data suggest a potential role of DDR signatures as an alternative mechanism to generate H-TMB in NS-pts. This preliminary observation could identify a subgroup of NS-pts responsive to IO and with a better prognosis.

1723P CLEC3B mRNA expression levels are linked to distinct genetic backgrounds, transcriptomic signatures and survival in NSCLC

Downregulated C-type lectin domain family 3 member B (CLEC3B) is observed in NSCLC and is linked with immune cell infiltration. We aimed to analyse the impact of CLEC3B mRNA expression on survival and its molecular link to NSCLC subtypes and to immune cell infiltration. 19,892 samples were tested at Caris Life Sciences (Phoenix, AZ) with NextGen Sequencing on DNA (592 genes/WES), RNA (WTS) and IHC. Top quartile transcripts per million (TPM) were defined as high (Q4, ≥4.03 TPM) and bottom quartile as low (Q1, ≤0.89 TPM). Cell infiltration was estimated by QuantiSEQ. X2/Fisher-Exact were used and significance was determined as p-value adjusted for multiple comparison (q<0.05). Real-world overall survival (OS) information was obtained from insurance claims data. Median age was 69 years. High CLEC3B mRNA expression was associated with female sex (55.2% women vs 44.8% men, p<0.001). Adenocarcinomas vs squamous-cell carcinomas had higher CLEC3B expression (2.28 vs 1.51, q<0.001). CLEC3B correlated negatively with mutations in TP53 (74.7% in Q1 vs 52.4% in Q4), KEAP1 (15.9% vs 11.2%), RB1 (13.5 vs 9.2%), CDKN2A (13.0% vs 8.3%), NF1 (10.3% vs 6.9%) (all q<0.001). KRAS (31.8% in Q4 vs 25.6% in Q1), EGFR (17.2% vs 8.1%), STK11 (15.9% vs 11.3%) mutations were more frequently observed in CLEC3B high expressors (all q<0.001). High CLEC3B mRNA expression was negatively associated with high TMB (43.0% vs 29.0%) and high PD-L1 expression (62.5% vs 47.7%) (all q<0.05). Transcriptomics revealed an upregulation of various immunological markers (i.e. LAG3, INF-G, PDCD1) and a higher abundance of several immune cells (i.e. B cells, macrophages, T cells) in the CLEC3B high subgroup (all q<0.001). Patients with high CLEC3B mRNA expression showed an improved OS when compared to CLEC3B low expression (p<0.001, HR: 1.35); a similar observation was made in patients treated with checkpoint inhibitors (p<0.001, HR: 1.29). Our study represents the largest analysis of CLEC3B mRNA expression in NSCLC. High CLEC3B expression levels are linked to a distinct molecular/immunological profile and to improved survival. Further experiments are now ongoing to unravel functional aspects of CLEC3B biology in NSCLC.