The six transcriptomic immune subtypes (ISs) (C1 - C6) were reported to have complex and different interplay between TME and cancer cells in TCGA (The Cancer Genome Atlas) pan-cancer cohort. Our study specifically explored how the consequence of interplay determines the prognosis and the response to therapy in LUAD cohorts. Clinical and molecular information of LUAD patients were from TCGA and Gene Expression Omnibus (GEO). The immune cell populations and gene/pathway enrichment analysis were performed to explore the molecular differences among the C3 IS and other ISs in the LUAD population. The proportion of C3 inflammatory IS was identified as the most common IS in both TCGA (N = 457) and GEO (N = 901) cohorts. The C3 IS was also found to be the most accurate prognostic subtype, which was associated with significantly longer OS (p <0.001) and DFS (p <0.001). The C3 IS presented higher levels of CD8 T, M1 macrophage, and myeloid dendritic cells, while lower levels of M2 macrophages and cancer-associated fibroblast cells. Moreover, the C3 subtype was enriched in the antigen process and presenting, interferon-gamma response, T cell receptor signaling, and natural killer cell-mediated cytotoxicity pathways than C1/C2. In contrast, the C1/C2 presented greater activation of pathways related to the cell cycles, DNA repair, and p53 signaling pathways. The immune-related C3 IS had a great ability to stratify the prognosis of LUAD, providing clues for further pathogenic research. This classification might help direct precision medicine screenings of LUAD patients, thus possibly improving their prognoses. 

/pdf/immune-subtypes-in-luad-identify-novel-tumor-2hfcljym.pdf

Immune Subtypes in LUAD Identify Novel Tumor Microenvironment Profiles With Prognostic and Therapeutic Implications

Although multiple studies have shown that loss of heterozygosity (LOH) at the human leukocyte antigen (HLA) locus is one of the mechanisms of immune escape, the effect of HLA LOH on the immunotherapy response of patients is still unclear. Based on the data of 425 Chinese lung cancer patients, the genomic characteristics with different HLA LOH statuses were analyzed. The driver genes mutation frequency, oncogenic signaling pathways mutation frequency, tumor mutational burden (TMB) and chromosomal instability (CIN) score in the HLA LOH high group was significantly higher than in the HLA LOH negative group. Transcriptome analyses revealed that pre-existing immunologically active tumor microenvironment (TME) was associated with HLA LOH negative patients. Non-small cell lung cancer (NSCLC) patients, especially for lung squamous cell carcinomas (LUSC), with HLA LOH negative have a longer survival period than those with HLA LOH. In addition, the combination of HLA LOH with TMB or programmed cell death-Ligand 1 (PD-L1) expression can further distinguish responders from non-responders. Furthermore, a comprehensive predictive model including HLA LOH status, TMB, PD-L1 expression and CD8+ T cells was constructed and exhibited a higher predictive value, which may improve clinical decision-making.

/pdf/integrated-investigation-of-the-prognostic-role-of-hla-loh-sz3h63dn.pdf

Integrated investigation of the prognostic role of HLA LOH in advanced lung cancer patients with immunotherapy

Small cell lung cancer is the most malignant subtype of lung cancer and has a poor prognosis. However, the mechanism is not well understood. The aim of this study was to investigate the characteristics of gene mutation in small cell lung cancer patients and the differences in HLA-I alleles between small cell lung cancer patients and healthy controls, and to explore the effects of gene mutations and specific HLA-I alleles on small-cell lung cancer from the perspective of immune regulation. Differences in HLA-I allele frequencies between the two groups were analyzed in a case-control study. Genetic testing was performed using target gene capture and sequencing method. The association between small cell lung cancer, HLA-I alleles, and gene mutation was analyzed by statistical methods. The small cell lung cancer group showed significantly higher HLA-A*11:02 (p < 0.001, OR = 4.693, 95%CI = 1.737–12.677), B*40:01 (p = 0.020, OR = 1.916, 95%CI = 1.101–3.333), and B*55:02 (p = 0.037, OR = 2.565, 95%CI = 1.027–6.408) and significantly lower B*44:03 (p = 0.015, OR = 0.196, 95%CI = 0.046–0.843) and C*06:02 (p = 0.005, OR = 0.369, 95%CI = 0.178–0.765) than the control group. Haplotype analysis results showed that HLA-A*11:01-B*51:01 (p = 0.044, OR = 3.433, 95%CI = 0.959–12.292), A*02:06-C*07:02 (p = 0.005, OR = 11.459, 95%CI = 1.331–98.689), A*11:01-C*07:02 (p = 0.007, OR = 3.040, 95%CI = 1.311–7.047), and B*46:01-C*01:02 (p = 0.048, OR = 2.310, 95%CI = 0.986–5.415) frequencies significantly increased and A*02:01-B*13:02 (p = 0.036, OR < 0.001, 95%CI = 0.000-0.918) and B*13:02-C*06:02 (p = 0.009, OR = 0.108, 95%CI = 0.014–0.810) frequency significantly decreased in small cell lung cancer patients. Three-locus haplotype analysis showed that the differences between small cell lung cancer patients and controls were not statistically significant. HLA-A*11:01, B*40:01, and B*55:02 may be the immune modulators associated with susceptibility and HLA-B*44:03 and C*06:02 act as the immune modulators associated with resistance of small cell lung cancer. Haplotypes HLA-A*11:01-B*51:01, A*02:06-C*07:02, A*11:01-C*07:02, and B*46:01-C*01:02 are positively associated with small cell lung cancer. Haplotypes A*02:01-B*13:02 and B*13:02-C*06:02 are negatively associated with small cell lung cancer.

pdf/small-cell-lung-cancer-relationship-with-hla-i-alleles-and-jauhn5ws72rm.pdf

Small cell lung cancer: relationship with HLA-I alleles and gene mutation

Detecting HLA loss of heterozygosity within a standard diagnostic sequencing workflow for prognostic and therapeutic opportunities

LRP1B in cancer: From a mutation landscape to predictive biomarkers for precision oncology

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

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

Popular Tasks used by Researchers

How can I help with your research?

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

We encountered an error while loading the panel. Please try refreshing the page.

Something went wrong

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

Anyone with the link can view this chat. You can switch it back to private anytime.

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Xiaoxiong Xiao

Author Tools

Chat about Author

Papers

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