HLA-DQB1 expression on tumor cells is a novel favorable prognostic factor for relapse in early-stage lung adenocarcinoma

Genomic and immune microenvironment features influencing chemoimmunotherapy response in gastric cancer with peritoneal metastasis: a retrospective cohort study

BACKGROUND

Patients with peritoneal metastasis (PM) from gastric cancer (GC) exhibit poor prognosis. Chemoimmunotherapy offers promising clinical benefits; however, its efficacy and predictive biomarkers in a conversion therapy setting remain unclear. The authors aimed to retrospectively evaluate chemoimmunotherapy efficacy in a conversion therapy setting for GC patients with PM and establish a prediction model for assessing clinical benefits.

MATERIALS AND METHODS

A retrospective evaluation of clinical outcomes encompassed 55 GC patients with PM who underwent chemoimmunotherapy in a conversion therapy setting. Baseline PM specimens were collected for genomic and transcriptomic profiling. Clinicopathological factors, gene signatures, and tumor immune microenvironment were evaluated to identify predictive markers and develop a prediction model.

RESULTS

Chemoimmunotherapy achieved a 41.8% objective response rate and 72.4% R0 resection rate in GC patients with PM. Patients with conversion surgery showed better overall survival (OS) than those without the surgery (median OS: not reached vs 7.82 m, P<0.0001). Responders to chemoimmunotherapy showed higher ERBB2 and ERBB3 mutation frequencies, CTLA4 and HLA-DQB1 expression, and CD8+ T cell infiltration, but lower CDH1 mutation and naïve CD4+ T cell infiltration, compared to nonresponders. A prediction model was established integrating CDH1 and ERBB3 mutations, HLA-DQB1 expression, and naïve CD4+ T cell infiltration (AUC=0.918), which were further tested using an independent external cohort (AUC=0.785).

CONCLUSION

This exploratory study comprehensively evaluated clinicopathological, genomic, and immune features and developed a novel prediction model, providing a rational basis for the selection of GC patients with PM for chemoimmunotherapy-involved conversion therapy.

HLA class II polymorphisms as prognostic biomarkers for right and left-sided colon cancer

BACKGROUND

Colon cancer (CC) is one of the most common malignancies worldwide. Characterization of new prognostic biomarkers for right-sided CC (RCC) and left-sided CC (LCC) may contribute to improving early detection. An association of human leukocyte antigens class II (HLA-II) with the predisposition to CC was suggested.

AIM OF THE STUDY

We evaluated the association of DRB1 and DQB1 with the risk of LCC and RCC.

PATIENTS AND METHODS

Our study comprised 93 CC patients and 100 healthy controls. Genotyping of HLA class II alleles were performed by the Polymerase Chain Reaction Sequence-Specific Primers (PCR-SSP).

RESULTS

DRB1*03 was positively associated with CC. In contrast, DRB1*11, DRB1*13, DQB1*03, and DQB1*05 were negatively linked to CC. Haplotype analysis revealed that DRB1*04-DQB1*04 and DRB1*09-DQB1*02 were positive, while DRB1*01-DQB1*05, DRB1*04-DQB1*03, DRB1*07-DQB1*02, DRB1*11-DQB1*03, DRB1*11-DQB1*05, and DRB1*13-DQB1*06 were negatively associated with CC. For sigmoid CC, DRB1*13, DRB1*11, and DQB1*05 were negative, while DRB1*04-DQB1*02, and DRB1*07-DQB1*03 were positively associated. DRB1*03 and DRB1*04-DQB1*04 were positive, while DRB1*11 and DQB1*03 were negatively linked to RCC. According to the LCC, DRB1*07, DRB1*11, DQB1*03, DQB1*05, and DRB1*07-DQB1*02 were negative. In contrast, DRB1*09-DQB1*02 was positively associated with LCC. Stratified analysis revealed that DRB1*11 is associated with higher risk of metastasis in CC and sigmoid CC, and tolerance to treatment in RCC. DQB1*03 was associated with lymph-node invasion in CC.

CONCLUSION

DRB1 and DQB1 polymorphisms could be used as future biomarkers for the early detection of subjects at a higher risk of developing RCC and LCC, metastasis in sigmoid CC, and tolerance to treatment in RCC.

Downregulation of pro-surfactant protein B contributes to the recurrence of early-stage non-small cell lung cancer by activating PGK1-mediated Akt signaling

Recurrence is one of the main causes of treatment failure in early-stage non-small cell lung cancer (NSCLC). However, there are no predictors of the recurrence of early-stage NSCLC, and the molecular mechanism of its recurrence is not clear. In this study, we used clinical sample analysis to demonstrate that low levels of expression of precursor surfactant protein B (pro-SFTPB) in primary NSCLC tissue compared to their adjacent tissues are closely correlated with recurrence and poor prognosis in early-stage NSCLC patients. In vitro and in vivo experiments showed that downregulation of pro-SFTPB expression activates the Akt pathway by upregulating PGK1, which promotes metastasis and tumorigenicity in NSCLC cells. We then demonstrated that pro-SFTPB suppresses the formation of the ADRM1/hRpn2/UCH37 complex by binding to ADRM1, which inhibits PGK1 deubiquitination, thus accelerating ubiquitin-mediated PGK1 degradation. In summary, our findings indicate that low expression of pro-SFTPB in primary NSCLC compared to their adjacent tissue has potential as a predictor of recurrence and poor prognosis in early-stage NSCLC. Mechanistically, downregulation of pro-SFTPB attenuates inhibition of ADRM1-deubiquitinated PGK1, resulting in elevated levels of PGK1 protein; this activates the Akt pathway, ultimately leading to the progression of early-stage NSCLC.

X or Y Cancer: An Extensive Analysis of Sex Differences in Lung Adenocarcinoma

Background: Cellular metabolism is a tightly controlled process during which cell growth and survival are maintained. Lung cancer is a disease with clear sex differences, where female patients have better survival rates than males. Evidence of sex differences is demonstrated in cancer risk, prognosis and response to different therapies, yet a sex-specific approach to cancer studies is not widely considered. These different tumour characteristics attributed to sex that impact disease outcome, including constitutional genetic and somatic molecular differences, make it essential to assess viral and hormonal influences. Methods: In silico analysis of lung adenocarcinoma (LUAD) TCGA data, including K-means clustering algorithm, dimensional reduction with principal component analysis and differential expression analysis using EdgeR (p < 0.05), were used to explore some robust sex differences in LUAD that exist in core signalling pathways and metabolic processes between males and females. The correlation of differentially expressed genes (DEGs) expression with immune abundance in the LUAD cohort was analysed on TIMER2.0 and adjusted by tumour purity utilising Cox proportional hazard. Multiple factorial analysis heatmap visualisation was used to examine endogenous steroid hormonal effects on LUAD patients with different smoking status and age groups. Results: We found 161 DEGs showing key differences in regulation of immune system and cellular homeostasis, key elements of divergent cancer progression, between the two sexes. We also found male and female LUAD patients to favour different metabolic intermediates for energy production to support tumourigenesis. Additionally, high levels of Tregs accompanied by DEGs correlated with better LUAD prognosis, and circulating hormonal transcriptional targets affect proliferation and progression in males and females differently. Finally, we examined the role of oestrogen protection in men and pre-/postmenopausal women. Conclusions: Further studies should focus on sex-specific changes and investigate sex-specific gene regulatory networks of these DEGs. Several lifestyle factors, including tobacco smoking and diet, differ between males and females. These factors might affect metabolic pathways and can influence the activity of epigenetic regulators, resulting in significant global epigenetic changes.

In silico identification of novel biomarkers for key players in transition from normal colon tissue to adenomatous polyps

Adenomatous polyps of the colon are the most common neoplastic polyps. Although most of adenomatous polyps do not show malign transformation, majority of colorectal carcinomas originate from neoplastic polyps. Therefore, understanding of this transformation process would help in both preventive therapies and evaluation of malignancy risks. This study uncovers alterations in gene expressions as potential biomarkers that are revealed by integration of several network-based approaches. In silico analysis performed on a unified microarray cohort, which is covering 150 normal colon and adenomatous polyp samples. Significant gene modules were obtained by a weighted gene co-expression network analysis. Gene modules with similar profiles were mapped to a colon tissue specific functional interaction network. Several clustering algorithms run on the colon-specific network and the most significant sub-modules between the clusters were identified. The biomarkers were selected by filtering differentially expressed genes which also involve in significant biological processes and pathways. Biomarkers were also validated on two independent datasets based on their differential gene expressions. To the best of our knowledge, such a cascaded network analysis pipeline was implemented for the first time on a large collection of normal colon and polyp samples. We identified significant increases in TLR4 and MSX1 expressions as well as decrease in chemokine profiles with mostly pro-tumoral activities. These biomarkers might appear as both preventive targets and biomarkers for risk evaluation. As a result, this research proposes novel molecular markers that might be alternative to endoscopic approaches for diagnosis of adenomatous polyps.

Exploration of Lung Cancer-Related Genetic Factors via Mendelian Randomization Method Based on Genomic and Transcriptomic Summarized Data

Lung carcinoma is one of the most deadly malignant tumors in mankind. With the rising incidence of lung cancer, searching for the high effective cures become more and more imperative. There has been sufficient research evidence that living habits and situations such as smoking and air pollution are associated with an increased risk of lung cancer. Simultaneously, the influence of individual genetic susceptibility on lung carcinoma morbidity has been confirmed, and a growing body of evidence has been accumulated on the relationship between various risk factors and the risk of different pathological types of lung cancer. Additionally, the analyses from many large-scale cancer registries have shown a degree of familial aggregation of lung cancer. To explore lung cancer-related genetic factors, Genome-Wide Association Studies (GWAS) have been used to identify several lung cancer susceptibility sites and have been widely validated. However, the biological mechanism behind the impact of these site mutations on lung cancer remains unclear. Therefore, this study applied the Summary data-based Mendelian Randomization (SMR) model through the integration of two GWAS datasets and four expression Quantitative Trait Loci (eQTL) datasets to identify susceptibility genes. Using this strategy, we found ten of Single Nucleotide Polymorphisms (SNPs) sites that affect the occurrence and development of lung tumors by regulating the expression of seven genes. Further analysis of the signaling pathway about these genes not only provides important clues to explain the pathogenesis of lung cancer but also has critical significance for the diagnosis and treatment of lung cancer.

A 10-gene prognostic signature points to LIMCH1 and HLA-DQB1 as important players in aggressive cervical cancer disease

BACKGROUND

Advanced cervical cancer carries a particularly poor prognosis, and few treatment options exist. Identification of effective molecular markers is vital to improve the individualisation of treatment. We investigated transcriptional data from cervical carcinomas related to patient survival and recurrence to identify potential molecular drivers for aggressive disease.

METHODS

Primary tumour RNA-sequencing profiles from 20 patients with recurrence and 53 patients with cured disease were compared. Protein levels and prognostic impact for selected markers were identified by immunohistochemistry in a population-based patient cohort.

RESULTS

Comparison of tumours relative to recurrence status revealed 121 differentially expressed genes. From this gene set, a 10-gene signature with high prognostic significance (p = 0.001) was identified and validated in an independent patient cohort (p = 0.004). Protein levels of two signature genes, HLA-DQB1 (n = 389) and LIMCH1 (LIM and calponin homology domain 1) (n = 410), were independent predictors of survival (hazard ratio 2.50, p = 0.007 for HLA-DQB1 and 3.19, p = 0.007 for LIMCH1) when adjusting for established prognostic markers. HLA-DQB1 protein expression associated with programmed death ligand 1 positivity (p < 0.001). In gene set enrichment analyses, HLA-DQB1high tumours associated with immune activation and response to interferon-γ (IFN-γ).

CONCLUSIONS

This study revealed a 10-gene signature with high prognostic power in cervical cancer. HLA-DQB1 and LIMCH1 are potential biomarkers guiding cervical cancer treatment.

Systematic analysis using a bioinformatics strategy identifies SFTA1P and LINC00519 as potential prognostic biomarkers for lung squamous cell carcinoma

Lung cancer has high incidence and mortality rates, in which lung squamous cell carcinoma (LUSC) is a primary type of non-small cell lung carcinoma (NSCLC). The aim of our study was to discover long non-coding RNAs (lncRNAs) associated with diagnose and prognosis for LUSC. RNA sequencing data obtained from LUSC samples were extracted from The Cancer Genome Atlas database (TCGA). Two prognosis-associated lncRNAs (including SFTA1P and LINC00519) were selected from LUSC samples, and the expression levels were also verified to be associated abnormal in LUSC clinical samples. Our findings demonstrate that lncRNAs SFTA1P and LINC00519 exert important functions in human LUSC and may serve as new targets for LUSC diagnosis and therapy.

Copy-Number Alteration Burden Differentially Impacts Immune Profiles and Molecular Features of Hepatocellular Carcinoma

PURPOSE

Chromosomal instability is a hallmark of cancer that results in broad and focal copy-number alterations (CNAs), two events associated with distinct molecular, immunologic, and clinical features. In hepatocellular carcinoma (HCC), the role of CNAs has not been thoroughly assessed. Thus, we dissected the impact of CNA burdens on HCC molecular and immune features.

EXPERIMENTAL DESIGN

We analyzed SNP array data from 452 paired tumor/adjacent resected HCCs and 25 dysplastic nodules. For each sample, broad and focal CNA burdens were quantified using CNApp, and the resulting broad scores (BS) and focal scores (FS) were correlated with transcriptomic, mutational, and methylation profiles, tumor immune composition, and clinicopathologic data.

RESULTS

HCCs with low broad CNA burdens (defined as BS ≤ 4; 17%) presented high inflammation, active infiltrate signaling, high cytolytic activity, and enrichment of the "HCC immune class" and gene signatures related to antigen presentation. Conversely, tumors with chromosomal instability (high broad CNA loads, BS ≥ 11; 40%), displayed immune-excluded traits and were linked to proliferation, TP53 dysfunction, and DNA repair. Candidate determinants of the low cytotoxicity and immune exclusion features of high-BS tumors included alterations in antigen-presenting machinery (i.e., HLA), widespread hypomethylation, and decreased rates of observed/expected neoantigenic mutations. High FSs were independent of tumor immune features, but were related to proliferation, TP53 dysfunction, and progenitor cell traits.

CONCLUSIONS

HCCs with high chromosomal instability exhibit features of immune exclusion, whereas tumors displaying low burdens of broad CNAs present an immune active profile. These CNA scores can be tested to predict response to immunotherapies.

Reverse engineering a predictive signature characterized by proliferation, DNA damage, and immune escape from stage I lung adenocarcinoma recurrence

Identifying early-stage cancer patients at risk for progression is a major goal of biomarker research. This report describes a novel 19-gene signature (19-GCS) that predicts stage I lung adenocarcinoma (LAC) recurrence and response to therapy and performs comparably in pancreatic adenocarcinoma (PAC), which shares LAC molecular traits. Kaplan-Meier, Cox regression, and cross-validation analyses were used to build the signature from training, test, and validation sets comprising 831 stage I LAC transcriptomes from multiple independent data sets. A statistical analysis was performed using the R language. Pathway and gene set enrichment were used to identify underlying mechanisms. 19-GCS strongly predicts overall survival and recurrence-free survival in stage I LAC (P=0.002 and P<0.001, respectively) and in stage I-II PAC (P<0.0001 and P<0.0005, respectively). A multivariate cox regression analysis demonstrated the independence of 19-GCS from significant clinical factors. Pathway analyses revealed that 19-GCS high-risk LAC and PAC tumors are characterized by increased proliferation, enhanced stemness, DNA repair deficiency, and compromised MHC class I and II antigen presentation along with decreased immune infiltration. Importantly, high-risk LAC patients do not appear to benefit from adjuvant cisplatin while PAC patients derive additional benefit from FOLFIRINOX compared with gemcitabine-based regimens. When validated prospectively, this proof-of-concept biomarker may contribute to tailoring treatment, recurrence reduction, and survival improvements in early-stage lung and pancreatic cancers.

Identification and validation of tumor microenvironment-related genes of prognostic value in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a major subtype of non-small cell lung cancer. Despite significant progress in its diagnosis and treatment, the mortality and morbidity rate of LUAD remains high worldwide. The aim of the present study was to perform a systematic investigation of the tumor microenvironment (TME) and identify TME-related genes of prognostic value in patients with LUAD. Firstly, the immune scores and stromal scores of patients with LUAD from The Cancer Genome Atlas were calculated using the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data algorithm, and a total of 281 prognostic TME-related genes were identified. Subsequently, functional analysis and protein-protein interaction network analysis revealed that these genes were mainly related to immune response, inflammatory response and chemotaxis. Finally, two independent LUAD cohorts from the Gene Expression Omnibus database were used to validate these genes, and 4 genes (GTPase IMAP family member 1, T-cell surface glycoprotein CD1b, integrin alpha-L and leukocyte surface antigen CD53) were identified, and downregulation of these genes was indicated to be associated with poor overall survival rate in patients with LUAD. In conclusion, a comprehensive analysis of TME was performed and 4 prognostic TME-related genes in patients with LUAD were identified.

STRIP2, a member of the striatin-interacting phosphatase and kinase complex, is implicated in lung adenocarcinoma cell growth and migration

Lung adenocarcinoma (LUAD) accounts for ~40% of lung cancer cases, and the 5-year relative survival rate is no more than 1%. Dysregulation of components of striatin-interacting phosphatase and kinase (STRIPAK) complexes is associated with various diseases, including cancer. Striatin-interacting protein 2 (STRIP2), also called Fam40b, has been reported to regulate tumor cell growth and migration. Here, we investigated the role of STRIP2 in LUAD growth, migration and the underlying mechanisms. Analysis of data from The Cancer Genome Atlas database revealed that STRIP2 is highly expressed and predicted poor outcomes in patients with LUAD. Moreover, quantitative RT-PCR (qRT-PCR) analysis revealed that the mRNA expression of STRIP2 is greater in all tested LUAD cells than in a normal lung cell line. To investigate the function of STRIP2, we overexpressed STRIP2 in SPC-A1 cells and depleted STRIP2 in Calu-3 cells. Cell proliferation was evaluated by Cell Counting Kit-8 and colony-forming assays, and Transwell assay was employed to test cell invasion and migration. Our results indicate that STRIP2 depletion suppressed cell proliferation, invasion and migration in Calu-3 cells, and overexpression of STRIP2 had the opposite effects in SPC-A1 cells. Moreover, we discovered that STRIP2 depletion reduced the protein levels of p-Akt and phosphorylated-mammalian target of rapamycin (p-mTOR) in Calu-3 cells, whereas STRIP2 overexpression increased levels of these proteins in SPC-A1 cells. Furthermore, we found that silencing of STRIP2 clearly enhanced protein levels of E-cadherin and reduced levels of N-cadherin, Vimentin and matrix metalloproteinase-9 in Calu-3 cells, whereas overexpression of STRIP2 had the opposite effect in SPC-A1 cells. Our data indicate that STRIP2 promotes the proliferation and motility of LUAD cells, and this may be mediated through the regulation of the Akt/mTOR pathway and epithelial-mesenchymal transition. These results may facilitate the development of therapeutic strategies to treat LUAD.

Development and validation of a 4-gene combination for the prognostication in lung adenocarcinoma patients

Objective: To identify a multi-gene prognostic factor in patients with lung adenocarcinoma (LUAD).

Materials and methods Prognosis-related genes were screened in the TCGA-LUAD cohort. Then, patients in this cohort were randomly separated into training set and test set. Least absolute shrinkage and selection operator (LASSO) regression was performed to the penalized the Cox proportional hazards regression (CPH) model on the training set, and a prognostication combination based on the result of LASSO analysis was developed. By performing Kaplan-Meier curve analysis, univariate and multivariable CPH model on the overall survival (OS) as well as recurrence free survival (RFS), the prognostication performance of the multigene combination were evaluated. Moreover, we constructed a nomogram and performed decision curve analysis to evaluate the clinical application of the multigene combination.

Results We obtained 99 prognosis-related genes and screened out a 4-gene combination (including CIDEC, ZFP3, DKK1, and USP4) according to the LASSO analysis. The results of survival analyses suggested that patients in the 4-gene combination low-risk group had better OS and RFS than those in the 4-gene combination high-risk group. The 4-gene mentioned was demonstrated to be independent prognostic factor of patients with LUAD in the training set(OS, HR=11.962, P<0.001; RFS, HR=9.281, P<0.001) and test set (OS, HR=5.377, P=0.003; RFS, HR=2.949, P=0.104). More importantly, its prognosis performance was well in the validation set (OS, HR=0.955, P=0.002; RFS, HR=1.042, P<0.001).

Conclusions We introduced a 4-gene combination which could predict the survival of LUAD patients and might be an independent prognostic factor in LUAD.