Wnt signaling pathway-derived score for predicting therapeutic resistance and tumor microenvironment in lung adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Due to tumor heterogeneity, understanding the pathological mechanism of tumor progression helps to improve the diagnosis process and clinical treatment strategies of LUAD patients. Methods: The transcriptome pattern, mutant expression and complete clinical information were obtained from the cancer genome atlas (TCGA) database and microarray data from gene expression omnibus (GEO) database. Firstly, we used single sample Gene Set Enrichment Analysis (ssGSEA) to estimate the activation of Wnt signaling pathway in each sample. Consensus clustering algorithm was used to classify LUAD samples into different subgroups according to the transcription patterns of 152 Wnt signaling pathway related genes. Then, ESTIMATE, ssGSEA and Gene Set Variation Analysis (GSVA) algorithms were used to assess the biological pathways and immunocytes infiltration between different subtypes. LASSO-COX algorithm was conducted to construct prognostic model. Kaplan-Meier and multivariate Cox analysis were performed to evaluate the predictive performance of risk model. Gene features were further confirmed using external datasets. Finally, we conducted vitro assay for validating hub gene (LEF1). Results: Based on the transcription patterns of 152 Wnt signaling pathway related genes, four different subtypes of LUAD patients were screened out by consensus clustering algorithm. Subsequently, it was found that patients with cluster A and B had massive immunocytes infiltration, and the survival rate of patients with cluster B was better than that of other subgroups. According to the coefficients in the LASSO- Cox model and the transcriptome patterns of these 18 genes, the risk score was constructed for each sample. The degree of malignancy of LUAD patients with high-risk subgroup was remarkable higher than that of patients with low-risk subgroup (p < 0.001). Subsequently, five top prognostic genes (AXIN1, CTNNB1, LEF1, FZD2, FZD4.) were screened, and their expression values were different between cancer and normal tissues. FZD2 and LEF1 were negatively related to ImmunoScore, and AXIN1 was negatively related to ImmunoScore. The significant correlation between LUAD patient risk score and overall survival (OS) was verified in external datasets. In the A549 cell line, knockdown of LEF1 can reduce the invasive and proliferation ability of LUAD cells. Conclusion: A innovative 18 genes predictive feature based on transcriptome pattern was found in patients with lung adenocarcinoma. These investigations further promote the insight of the prognosis of lung adenocarcinoma and may contribute to disease management at risk stratification.

Programmed Death Ligand-1 Expression in Gliomas: A Study of Histopathological and Molecular Associations

Background

Gliomas are aggressive tumors with limited treatment options. Immunotherapy targets are under evaluation as new therapeutic targets in gliomas.

Aims and Objectives

The aims of the study were to analyze expression of PDL1 in adult diffuse gliomas in World Health Organization grade II, III, and IV and to corelate its expression with demographic features, IDH-1, ATRX, and p-53 mutation status.

Materials and Methods

This was a case series that included 30 cases of adult diffuse glioma. In all cases, a composite diagnosis including histologic type, grade, and molecular alterations was rendered. PDL1 testing was done by immunohistochemistry using PDL1 SP-263 antibody.

Results

PDL1 expression was identified in 33.3% cases in tumor cells and in 6.67% cases in immune cells. All neoplasms with PDL1 expression were astrocytic tumors. PDL1 expression was significantly associated with IDH-1 immunonegative gliomas (P = 0.013).

Conclusion

PDL1 is a novel therapeutic target in gliomas. The current study is an attempt to evaluate the expression of PDL1 over the varied spectrum of gliomas.

Genomic analyses of high-grade neuroendocrine gynecological malignancies reveal a unique mutational landscape and therapeutic vulnerabilities

High‐grade neuroendocrine carcinoma of gynecologic origin (NEC‐GYN) is a highly aggressive cancer that often affects young women. The clinical management of NEC‐GYN is typically extrapolated from its counterpart, small cell carcinoma of the lung (SCLC), but, unfortunately, available therapies have limited benefit. In our NEC‐GYN cohort, median progression‐free survival (PFS) and overall survival (OS) were 1 and 12 months, respectively, indicating the highly lethal nature of this cancer. Our comprehensive genomic analyses unveiled that NEC‐GYN harbors a higher mutational burden with distinct mutational landscapes from SCLC. We identified 14 cancer driver genes, including the most frequently altered KMT2C (100%), KNL1 (100%), NCOR2 (100%), and CCDC6 (93%) genes. Transcriptomic analysis identified several novel gene fusions; astonishingly, the MALAT1 lincRNA gene was found in ˜ 20% of all fusion events in NEC‐GYN. Furthermore, NEC‐GYN exhibited a highly immunosuppressive state, intact RB1 expression, and was uniquely enriched with the YAP1^high molecular subtype. Our study identifies several potential therapeutic targets and suggests an urgent need to re‐evaluate the treatment options for NEC‐GYN.

pMHC Structural Comparisons as a Pivotal Element to Detect and Validate T-Cell Targets for Vaccine Development and Immunotherapy-A New Methodological Proposal

The search for epitopes that will effectively trigger an immune response remains the “El Dorado” for immunologists. The development of promising immunotherapeutic approaches requires the appropriate targets to elicit a proper immune response. Considering the high degree of HLA/TCR diversity, as well as the heterogeneity of viral and tumor proteins, this number will invariably be higher than ideal to test. It is known that the recognition of a peptide-MHC (pMHC) by the T-cell receptor is performed entirely in a structural fashion, where the atomic interactions of both structures, pMHC and TCR, dictate the fate of the process. However, epitopes with a similar composition of amino acids can produce dissimilar surfaces. Conversely, sequences with no conspicuous similarities can exhibit similar TCR interaction surfaces. In the last decade, our group developed a database and in silico structural methods to extract molecular fingerprints that trigger T-cell immune responses, mainly referring to physicochemical similarities, which could explain the immunogenic differences presented by different pMHC-I complexes. Here, we propose an immunoinformatic approach that considers a structural level of information, combined with an experimental technology that simulates the presentation of epitopes for a T cell, to improve vaccine production and immunotherapy efficacy.

Quantitative Proteomics and Metabolomics Reveal Biomarkers of Disease as Potential Immunotherapy Targets and Indicators of Therapeutic Efficacy

Quantitative mass spectrometry (MS) continues to deepen our understanding of the immune system, quickly becoming the gold standard for obtaining high-throughput, quantitative data on biomolecules. The development of targeted and multiplexed assays for biomarker quantification makes MS an attractive tool both for diagnosing diseases and for quantifying the effects of immunotherapeutics. Because of its accuracy, the use of MS for identifying biomarkers of disease reduces the potential for misdiagnosis and overtreatment. Advances in workflows for sample processing have drastically reduced processing time and complexities due to sample preparation, making MS a more accessible technology. In this review, we present how recent developments in proteomics and metabolomics make MS an essential component of enhancing and monitoring the efficacy of immunotherapeutic treatments.

Cancer/testis antigen-Plac1 promotes invasion and metastasis of breast cancer through Furin/NICD/PTEN signaling pathway

Placenta‐specific protein 1 (Plac1) is a cancer/testis antigen that plays a critical role in promoting cancer initiation and progression. However, the clinical significance and mechanism of Plac1 in cancer progression remain elusive. Here, we report that Plac1 is an important oncogenic and prognostic factor, which physically interacts with Furin to drive breast cancer invasion and metastasis. We have shown that Plac1 expression positively correlates with clinical stage, lymph node metastasis, hormone receptor status, and overall patient survival. Overexpression of Plac1 promoted invasion and metastasis of breast cancer cells in vitro and in vivo. Co‐immunoprecipitation and immunofluorescence cell staining assays revealed that interaction of Plac1 and Furin degraded Notch1 and generated Notch1 intracellular domain (NICD) that could inhibit PTEN activity. These findings are consistent with the results of microarray study in MDA‐MB‐231 cells overexpressing Plac1. A rescue study showed that inhibition of Furin and overexpression of PTEN in Plac1 overexpression cells blocked Plac1‐induced tumor cell progression. Taken together, our findings suggest that functional interaction between Plac1 and Furin enhances breast cancer invasion and metastasis and the Furin/NICD/PTEN axis may act as an important therapeutic target for breast cancer treatment.