ABSTRACT
@#Objective To analyze the expression and clinical treatment and prognosis assessment significance of FAM83H-AS1 in breast cancer by bioinformatics analysis.Methods The expression of FAM83H-AS1 in various cancer types was analyzed in the Cancer Genome Atlas(TCGA)database by R language.Additionally the expression in breast cancer was examined by Gene Expression Profiling Interactive Analysis(GEPIA)online database.Survival data were downloaded from TCGA to analyze the correlation between FAM83H-AS1 expression levels and prognosis among breast cancer patients.GEPIA and Kaplan-Meier Plotter were used for dual verification.Clinical information was obtained from TCGA for further analysis on the relationship between FAM83H-AS1 and clinical characteristics.And the relationship between FAM83H-AS1 and tumor microenvironment,immunodetection point-related genes and tumor mutation burden(TMB)was analyzed using R language.Gene set enrichment analysis(GSEA)was performed.Results The expression of FAM83H-AS1 was abnormal in many cancers,particularly exhibiting a significant increase in breast cancer.High expression of FAM83H-AS1 is associated with significantly reduced overall survival in breast cancer patients.Furthermore,the expression level of FAM83H-AS1 varies among breast cancer patients with different clinical stages.FAM83H-AS1 exhibits negative correlation with stromal cell score and immune cell score in breast cancer samples,and correlated with immune detection point-related gene.TMB radar map results suggest that the expression of FAM83H-AS1 in breast cancer is positively correlated with tumor mutational burden.GSEA revealed a positive correlation between the expression of FAM83H-AS1 and the function of mismatch repair.Conclusion FAM83H-AS1 is highly expressed in breast cancer,and is related to poor prognosis.Its expression correlates with clinicopathological stage,tumor microenvironment and TMB of breast cancer patients.Furthermore,FAM83H-AS1 exhibits associations with certain immune checkpoint-related genes and mismatch repair genes.These findings provide a important theoretical basis for clinical treatment,prognosis prediction and development of gene-target drugs.
ABSTRACT
Medical studies have found that tumor mutation burden (TMB) is positively correlated with the efficacy of immunotherapy for non-small cell lung cancer (NSCLC), and TMB value can be used to predict the efficacy of targeted therapy and chemotherapy. However, the calculation of TMB value mainly depends on the whole exon sequencing (WES) technology, which usually costs too much time and expenses. To deal with above problem, this paper studies the correlation between TMB and slice images by taking advantage of digital pathological slices commonly used in clinic and then predicts the patient TMB level accordingly. This paper proposes a deep learning model (RCA-MSAG) based on residual coordinate attention (RCA) structure and combined with multi-scale attention guidance (MSAG) module. The model takes ResNet-50 as the basic model and integrates coordinate attention (CA) into bottleneck module to capture the direction-aware and position-sensitive information, which makes the model able to locate and identify the interesting positions more accurately. And then, MSAG module is embedded into the network, which makes the model able to extract the deep features of lung cancer pathological sections and the interactive information between channels. The cancer genome map (TCGA) open dataset is adopted in the experiment, which consists of 200 pathological sections of lung adenocarcinoma, including 80 data samples with high TMB value, 77 data samples with medium TMB value and 43 data samples with low TMB value. Experimental results demonstrate that the accuracy, precision, recall and F1 score of the proposed model are 96.2%, 96.4%, 96.2% and 96.3%, respectively, which are superior to the existing mainstream deep learning models. The model proposed in this paper can promote clinical auxiliary diagnosis and has certain theoretical guiding significance for TMB prediction.
Subject(s)
Humans , Lung Neoplasms/pathology , Carcinoma, Non-Small-Cell Lung/genetics , Mutation , Adenocarcinoma of Lung/genetics , Biomarkers, Tumor/geneticsABSTRACT
Blood-based tumor mutational burden (bTMB) calculated based on next-generation sequencing (NGS) to examine the circulating tumor DNA (ctDNA) is often considered as a non-invasive biomarker-candidate predicting the clinical benefit of patients who received immunotherapy. Some recent evidence indicates that the alteration of bTMB related characters is often associated with objective response rates of patients to cancer immunotherapy, but has limited predictive value in long-term prognostic benefit. The predictive efficacy of bTMB is affected by many factors such as the abundance of circulating tumor DNA and tumor heterogeneity, and adjusted bTMB examination after correcting for interfering factors can better predict the long-term survival benefit of immunotherapy. Application of bTMB testing still needs to overcome methodological, economic, and standardization challenges during clinical application.
ABSTRACT
Recently, great breakthroughs have been made in the treatment of melanoma with immune checkpoint inhibitors. However, only a small proportion of patients show a long-lasting response to immunotherapy, and risks of immune-related adverse events and drug resistance have been also increasing along with the emergence of combination treatment. This review summarizes biomarkers related to the efficacy of immune checkpoint inhibitors in the treatment of melanoma, aiming to predict and screen out patients who may benefit from immunotherapy, guide individualized clinical treatment, and reduce the occurrence of drug resistance and adverse reactions.
ABSTRACT
We explored clinicopathological features and treatment strategies for thoracic SMARCA4-deficient undifferentiated tumor (SMARCA4-UT). Thoracic SMARCA4-UT is a new entity recently acknowledged in the 2021 edition of World Health Organization Classification of Thoracic Tumors, and doctors are relatively unfamiliar with its diagnosis, treatment, and prognosis. Taking a case of SMARCA4-UT treated in Peking University First Hospital as an example, this multi-disciplinary discussion covered several hot issues on diagnosing and treating thoracic SMARCA4-UT, including histological features, immu- nohistochemical and molecular phenotype, immune checkpoint inhibitor (ICI) therapy, and pathological assessment of neoadjuvant therapy response. The patient was an older man with a long history of smoking and was admitted due to a rapidly progressing solid tumor in the lower lobe of the right lung. Histologically, tumor cells were epithelioid, undifferentiated, diffusely positive for CD34, and partially positive for SALL4.The expression of BRG1 protein encoded by SMARCA4 gene was lost in all of tumor cells, and next-generation sequencing(NGS)confirmed SMARCA4 gene mutation (c.2196T>G, p.Y732Ter). The pathological diagnosis reached as thoracic SMARCA4-UT, and the preoperative TNM stage was T1N2M0 (ⅢA). Tumor proportion score (TPS) detected by immunohistochemistry of programmed cell death 1-ligand 1 (PD-L1, clone SP263) was 2%. Tumor mutation burden (TMB) detected by NGS of 1 021 genes was 16. 3/Mb. Microsatellite detection showed the tumor was microsatellite stable (MSS). Neo-adjuvant therapy was implemented with the combined regimen of chemotherapy and ICI. Right lower lobectomy was performed through thoracoscopy after the two weeks' neoadjuvant. The pathologic assessment of lung tumor specimens after neoadjuvant therapy revealed a complete pathological response (CPR). The post-neoadjuvant tumor TNM stage was ypT0N0M0. Then, five cycles of adjuvant therapy were completed. Until October 2022, neither tumor recurrence nor metastasis was detected, and minimal residual disease (MRD) detection was negative. At present, it is believed that if BRG1 immunohistochemical staining is negative, regardless of whether SMARCA4 gene mutation is detected, it should be classified as SMARCA4-deficient tumors. SMARCA4-deficient tumors include a variety of carcinomas and sarcomas. The essential criteria for diagnosing SMARCA4-UT includes loss of BRG1 expression, speci-fic histological morphology, and exclude other common thoracic malignant tumors with SMARCA4-deficiency, such as squamous cell carcinoma, adenocarcinoma and large cell carcinoma. SMARCA4-UT is a very aggressive malignant tumor with a poor prognosis. It has almost no targeted therapy mutations, and little response to chemotherapy, but ICI is currently the only effective drug. The successful diagnosis and treatment for this case of SMARCA4-UT should enlighten significance for various kinds of SMARCA4-deficient tumors.
Subject(s)
Humans , Immune Checkpoint Inhibitors , Neoplasm Recurrence, Local , Lung Neoplasms/genetics , Thoracic Neoplasms/pathology , Adenocarcinoma , DNA Helicases , Nuclear Proteins , Transcription FactorsABSTRACT
Objective:To explore the genes and molecular markers related to the sensitivity to concurrent chemoradiotherapy in patients with locally advanced esophageal squamous cell carcinoma.Methods:The peripheral blood sample of 31 patients with locally advanced esophageal squamous cell carcinoma receiving radical concurrent chemoradiotherapy was collected and the plasma circulating free DNA (cf-DNA) was extracted before treatment. The target gene capture sequencing technology based on NovaseQ6000 high-throughput sequencing platform was employed to detect the changes of target genes and tumor mutation burden (TMB). According to the short-term efficacy of chemoradiotherapy, all patients were divided into the chemoradiotherapy-sensitive group (CR+ PR) and chemoradiotherapy-resistant group (SD+ PD). Bioinformatics and clinical data were adopted to analyze the differences of gene mutation and TMB between two groups.Results:In the sequencing data of 31 patients, the tumor-related genes with a mutation frequency above 10% were Tp53, Notch1, BRAF, FGFR4, CDKN2A, ATRX and Axin2, which were almost equally distributed between the CR+ PR and SD+ PD groups. High-frequency mutant genes were associated with 7 signaling pathways, mainly involved in the RTK/RAS signaling pathways. The TMB value in the CR+ PR group was higher than that in the SD+ PD group ( P=0.04), however, the mutation rate of GXYLT1 and KRT18 genes in the SD+ PD group was higher than that in the CR+ PR group ( P<0.05). Conclusions:Tp53, Notch1 and CDKN2A may be the high-frequency mutant genes associated with the incidence and progression of esophageal squamous cell carcinoma. KRT18, GXYLT1 and TMB are closely correlated with the sensitivity to concurrent chemoradiotherapy of patients with locally advanced esophageal squamous cell carcinoma.
ABSTRACT
Programmed death ligand 1 (PD-L1) is a well known biomarker for targeted immunotherapy. However, the relationship between the expression of PD-L1 and the immunotherapy efficacy is not always consistent in different cases. Some patients who are PD-L1 negative still can benefit from immunosuppressive therapy, while some non-small cell lung cancer (NSCLC) patients with PD-L1 positive, even strongly positive, can not. Therefore, PD-L1 is not a completely reliable immunotherapy biomarker. Tumor mutation burden (TMB) estimated by whole exome sequencing (WES) is a biomarker recently approved by Food and Drug Administration (FDA). In this paper, we briefly reviewed the factors that result in the variaty of TMB in order to improve the reliability of the TMB and help clinicians to select patients who can get benefit from immunotherapy more wisely. .
ABSTRACT
Objective To investigate the relation between TMB and the efficiency of PD-1/PD-L1 inhibitors treatment for non-small-cell lung cancer. Methods Studies were searched from PubMed, Embase, Cochrane Library database, Chinese Biomedical Literature Database and Wanfang Database up to March 25, 2020. RevMan 5.3 software and STATA15.0 were used for analysis. Results Twelve literatures were involved, including 1209 patients. TMB significantly improved PFS (HR=0.54, 95%CI: 0.42-0.70, P < 0.001) but reduced the ORR (OR=4.41, 95%CI: 2.54-7.63, P < 0.001) of NSCLC patients treated with PD-1/PD-L1 inhibitors. The subgroup analyses showed that the predictive value of TMB was significant in non-small cell lung cancer treated by PD-1/PD-L1 inhibitors combined with anti-CTLA-4 therapy or chemotherapy. No significant publication bias was observed by the Begg's test and Egger's test. Conclusion High tumor mutation burden may predict the improved PFS of non-small cell lung cancer by PD-1/PD-L1 inhibitors treatment, but its predictive value for OS, ORR and long-term survival need more exploration.
ABSTRACT
Objective To study the correlations between tumor mutation burden (TMB) and the prognosis of hepatocellular carcinoma (HCC) patients,and to investigate the effect of TMB on differential expression genes of HCC and the proportion of invasive immune cells in tumor tissues.Methods The somatic variation data,gene transcriptional expression data and clinical information of HCC patients were obtained from the cancer genome atlas (TCGA) database.The R program language (version 3.6.1)maftools function package was used to analyze the gene mutation data characteristics of the samples.The TMB value of each sample was calculated using the full-exon sequencing data of patients with hepatocellular carcinoma on the VarScan2 platform,sorted by TMB value,and the median value was used to divide all samples into high TMB and low TMB groups.Kaplan-Meier method was used to draw the survival curves of two groups of patients and log-rank test was performed to determine the correlation between tumor mutation load and prognosis.The Limma function package of R language was used to screen the differentially expressed genes between the two groups (FDR =0.05 and logFC =1),and the clusterProfiler function package of R language was used to perform gene ontology (GO) enrichment analysis of the differential genes and kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis (screening criteria were all P < 0.05).Then the CIBERSORT tool was used to compare and analyze the difference in the proportion of invasive immune cells between the two groups.Results A total of 364 patients with HCC from TCGA database were included in the study.Mutations were found in 327 (84%) samples,and there was a synergistic correlation between OBSCN and FLG mutations (P < 0.05),while mutations in CTNNB1 and AXIN1 are mutually exdusive (P < 0.05).A total of 363 patients were included in the TMB survival analysis,sorted by the size of TMB value.All samples were divided into high TMB group (182 cases) and low TMB group (181 cases) with the median value.We found that TMB had no significant effect on the prognosis of HCC patients (P > 0.05).A total of 198 with differentially expressed genes (28 up-regulated genes and 170 down-regulated genes) were screened between the high TMB group and the low TMB group.In GO analysis,it was found that the differentially expressed genes were mainly enriched in extracellular matrix tissues,extracellular structural tissues,extracellular matrix,extracellular matrix containing collagen,extracellular matrix structural components and other functions.In KEGG analysis,differential genes were highly enriched in extracellular matrix receptor interaction pathway and adhesive plaque pathway.In the correlation analysis of the proportion of infiltrating immune cells,CD4 + memory T cells were more infiltrating in the low TMB group (P < 0.05).Monocytes showed a higher degree of infiltration in the high TMB group (P < 0.05).Conclusion There was no correlation between TMB and the prognosis of HCC patients.TMB has significant influence on the differential expression genes of HCC and the proportion of invasive immune cells in tumor tissues.
ABSTRACT
Immunotherapy has become the fourth cancer therapy after surgery, chemotherapy, and radiotherapy. In particular, immune checkpoint inhibitors are proved to be unprecedentedly in increasing the overall survival rates of patients with refractory cancers, such as advanced melanoma, non-small cell lung cancer, and renal cell carcinoma. However, inhibitor therapies are only effective in a small proportion of patients with problems, such as side effects and high costs. Therefore, doctors urgently need reliable predictive biomarkers for checkpoint inhibitor therapies to choose the optimal therapies. Here, we review the biomarkers that can serve as potential predictors of the outcomes of immune checkpoint inhibitor treatment, including tumor-specific profiles and tumor microenvironment evaluation and other factors.
Subject(s)
Humans , Autoantibodies , Blood , Allergy and Immunology , Biomarkers, Tumor , Blood , Allergy and Immunology , Immunotherapy , Neoplasms , Blood , Therapeutics , Tumor MicroenvironmentABSTRACT
The morbidity and mortality of lung cancer is the first in the world, immunotherapy has become a important treatment strategy in addition to chemotherapy, radiotherapy and targeted therapy. In recent years, the US Food and Drug Administration (FDA) has successively approved immunological checkpoint inhibitors as standard programs for non-small cell lung cancer (NSCLC) in second-line or first-line treatment. The National Comprehensive Cancer Network (NCCN) also recommends immunological checkpoint inhibitors as the standard treatment for small cell lung cancer (SCLC). Now, the treatment for lung cancer has entered the era of precision treatment, it is very important to select effective and reliable biomarker for the dominant populations of lung cancer to receive immunotherapy. A large number of researchs indicated that tumor mutation burden (TMB) may be an independent predicted biomarker for immunotherapy, but with limitations. This article reviewed the predictive value of TMB and its limitations in the field of immunotherapy for lung cancer.
Subject(s)
Animals , Humans , Biomarkers , Metabolism , Immunologic Factors , Immunotherapy , Lung Neoplasms , Drug Therapy , Genetics , Metabolism , Mutation , Tumor BurdenABSTRACT
Small-cell lung cancer (SCLC) has a high degree of malignancy and is characterized by strong invasiveness, rapid growth, and early metastasis. SCLC is sensitive to initial treatment with chemotherapy and radiotherapy, but it can easily relapse and has a poor prognosis. Both programmed death-1 (PD-1) and programmed cell death-ligand 1 (PD-L1) antagonists activate the immune response of tumor cells by activating T cells, and have shown exciting curative effects in clinical studies of SCLC, thereby becoming powerful po-tential agents to treat SCLC in the future. This article aims to illustrate the progress of PD-1/PD-L1 inhibitors in the treatment of SCLC, as well as the role of PD-L1 expression and tumor mutation burden (TMB) as a biomarker in SCLC.
ABSTRACT
With the advancement of high-throughput sequencing technology, improvements in big data processing and analysis have been witnessed. Evaluation of anti-tumor effects of targeted therapy and immunotherapy using various molecular markers based on high-throughput sequencing and big data are moving towards clinical application. Panel detection of different genetic markers pro-vides the basis for cancer diagnosis and treatment. In this article, the classification of high-throughput sequencing panel, application of large panel in cancer diagnosis, targeted therapy, immunotherapy, and the problems encountered in the clinical application of large panels are reviewed in order to provide a reference for their clinical application and promote the advancement of precision medicine.
ABSTRACT
Endometrial cancer is one of the three common cancer of the female genital tract. According to the molecular char-acteristics of endometrial cancer.The cancer genome atlas proposed four molecular subtypes:POLE (DNA polymerase ε,POLE) mutant;microsatellite instability hypermutation;low copy number and high copy number/serous. Numerous preclinical and clinical researches indicated that PD-1/PD-L1 blockade therapy is a promising method for immunotherapy of endometrial cancer. The subtypes of POLE mutant and MSI hypermutation in endometrial cancers are characterized by high tumor mutation burden which may benefit from the treatment of PD-1/PD-L1 blockade. This molecular classification of endometrial cancer provides a new clinical treatment strategy for individualized immunotherapy.