IGLL5 is correlated with tumor-infiltrating immune cells in clear cell renal cell carcinoma

Bioinformatics analysis of the role of lysosome-related genes in breast cancer

This study aimed to investigate the roles of lysosome-related genes in BC prognosis and immunity. Transcriptome data from TCGA and MSigDB, along with lysosome-related gene sets, underwent NMF cluster analysis, resulting in two subtypes. Using lasso regression and univariate/multivariate Cox regression analysis, an 11-gene signature was successfully identified and verified. High- and low-risk populations were dominated by HR+ sample types. There were differences in pathway enrichment, immune cell infiltration, and immune scores. Sensitive drugs targeting model genes were screened using GDSC and CCLE. This study constructed a reliable prognostic model with lysosome-related genes, providing valuable insights for BC clinical immunotherapy.

Breast cancer clinical outcomes and tumor immune microenvironment: cross-dialogue of multiple epigenetic modification profiles

The discovery of RNA methylation alterations associated with cancer holds promise for their utilization as potential biomarkers in cancer diagnosis, prognosis, and prediction. RNA methylation has been found to impact the immunological microenvironment of tumors, but the specific role of methylation-related genes (MRGs), particularly in breast cancer (BC), the most common cancer among women globally, within the tumor microenvironment remains unknown. In this study, we obtained data from TCGA and GEO databases to investigate the expression patterns of MRGs in both genomic and transcriptional domains in BC. By analyzing the data, we identified two distinct genetic groupings that were correlated with clinicopathological characteristics, prognosis, degree of TME cell infiltration, and other abnormalities in MRGs among patients. Subsequently, an MRG model was developed to predict overall survival (OS) and its accuracy was evaluated in BC patients. Additionally, a highly precise nomogram was created to enhance the practical usability of the MRG model. In low-risk groups, we observed lower TBM values and higher TIDE scores. We further explored how MRGs influence a patient's prognosis, clinically significant characteristics, response to therapy, and the TME. These risk signatures have the potential to improve treatment strategies for BC patients and could be applied in future clinical settings. Moreover, they may also be utilized to determine prognosis and biological features in these patients.

Mutational signatures and their association with survival and gene expression in urological carcinomas

Different sources of mutagenesis cause consistently identifiable patterns of mutations and mutational signatures that mirror the various carcinogenetic processes. We used publicly available data from the Cancer Genome Atlas to evaluate the associations between the activity of the mutational signatures and various survival endpoints in six types of urological cancers after adjusting for established prognostic factors. The predictive power of the signatures was evaluated with dynamic area under curve models. In addition, links between mutational signature activities and differences in gene expression patterns were analysed. APOBEC-related signature SBS2 was associated with improved overall survival (OS) and disease-specific survival (DSS) in bladder carcinomas in the multivariate analysis, while clock-like signature SBS1 predicted shortened DSS and progression-free interval (PFI) in clear cell renal cell carcinomas (ccRCC). In papillary renal cell carcinomas (pRCC), SBS45 was a predictor of improved outcomes, and APOBEC-related SBS13 was a predictor of worse outcomes. Gene expression analyses revealed various enriched pathways between the low- and high-signature groups. Interestingly, in both the ccRCC and pRCC cohorts, the genes of several members of the melanoma antigen (MAGE) family were highly upregulated in the signatures, which predicted poor outcomes, and downregulated in signatures, which were associated with improved survival. To summarize, SBS signatures provide substantial prognostic value compared with just the traditional prognostic factors in certain cancer types. APOBEC-related SBS2 and SBS13 seem to provide robust prognostic information for particular urological cancers, maybe driven by the expression of specific groups of genes, including the MAGE gene family.

Immunological modifications following chemotherapy are associated with delayed recurrence of ovarian cancer

Introduction

Ovarian cancer recurs in most High Grade Serous Ovarian Cancer (HGSOC) patients, including initial responders, after standard of care. To improve patient survival, we need to identify and understand the factors contributing to early or late recurrence and therapeutically target these mechanisms. We hypothesized that in HGSOC, the response to chemotherapy is associated with a specific gene expression signature determined by the tumor microenvironment. In this study, we sought to determine the differences in gene expression and the tumor immune microenvironment between patients who show early recurrence (within 6 months) compared to those who show late recurrence following chemotherapy.

Methods

Paired tumor samples were obtained before and after Carboplatin and Taxol chemotherapy from 24 patients with HGSOC. Bioinformatic transcriptomic analysis was performed on the tumor samples to determine the gene expression signature associated with differences in recurrence pattern. Gene Ontology and Pathway analysis was performed using AdvaitaBio's iPathwayGuide software. Tumor immune cell fractions were imputed using CIBERSORTx. Results were compared between late recurrence and early recurrence patients, and between paired pre-chemotherapy and post-chemotherapy samples.

Results

There was no statistically significant difference between early recurrence or late recurrence ovarian tumors pre-chemotherapy. However, chemotherapy induced significant immunological changes in tumors from late recurrence patients but had no impact on tumors from early recurrence patients. The key immunological change induced by chemotherapy in late recurrence patients was the reversal of pro-tumor immune signature.

Discussion

We report for the first time, the association between immunological modifications in response to chemotherapy and the time of recurrence. Our findings provide novel opportunities to ultimately improve ovarian cancer patient survival.

Single-nucleus RNA sequencing and deep tissue proteomics reveal distinct tumour microenvironment in stage-I and II cervical cancer

BACKGROUND

Cervical cancer (CC) is the 3rd most common cancer in women and the 4th leading cause of deaths in gynaecological malignancies, yet the exact progression of CC is inconclusive, mainly due to the high complexity of the changing tumour microenvironment (TME) at different stages of tumorigenesis. Importantly, a detailed comparative single-nucleus transcriptomic analysis of tumour microenvironment (TME) of CC patients at different stages is lacking.

METHODS

In this study, a total of 42,928 and 29,200 nuclei isolated from the tumour tissues of stage-I and II CC patients and subjected to single-nucleus RNA sequencing (snRNA-seq) analysis. The cell heterogeneity and functions were comparatively investigated using bioinformatic tools. In addition, label-free quantitative mass spectrometry based proteomic analysis was carried out. The proteome profiles of stage-I and II CC patients were compared, and an integrative analysis with the snRNA-seq was performed.

RESULTS

Compared with the stage-I CC (CCI) patients, the immune response relevant signalling pathways were largely suppressed in various immune cells of the stage-II CC (CCII) patients, yet the signalling associated with cell and tissue development was enriched, as well as metabolism for energy production suggested by the upregulation of genes associated with mitochondria. This was consistent with the quantitative proteomic analysis that showed the dominance of proteins promoting cell growth and intercellular matrix development in the TME of CCII group. The interferon-α and γ responses appeared the most activated pathways in many cell populations of the CCI patients. Several collagens, such as COL12A1, COL5A1, COL4A1 and COL4A2, were found significantly upregulated in the CCII group, suggesting their roles in diagnosing CC progression. A novel transcript AC244205.1 was detected as the most upregulated gene in CCII patients, and its possible mechanistic role in CC may be investigated further.

CONCLUSIONS

Our study provides important resources for decoding the progression of CC and set the foundation for developing novel approaches for diagnosing CC and tackling the immunosuppressive TME.

Characterization of clonal immunoglobulin heavy V-D-J gene rearrangements in Chinese patients with chronic lymphocytic leukemia: Clinical features and molecular profiles

Introduction

Several prognostic factors of chronic lymphocytic leukemia (CLL) have been identified, such as cytogenetic aberrations and recurrent gene mutations. B-cell receptor (BCR) signaling plays an important role in the tumorigenesis of CLL, and its clinical significance in predicting prognosis is also under study.

Methods

Therefore, we assessed the already-known prognostic markers, immunoglobulin heavy chain (IGH) gene usage and the associations among these factors in 71 patients diagnosed with CLL in our center from October 2017 to March 2022. Sequencing of IGH gene rearrangements was performed using Sanger sequencing or IGH-based next-generation sequencing, and the results were further analyzed for distinct IGH/IGHD/IGHJ genes and the mutational status of the clonotypic IGHV (IGH variable) gene.

Results

In summary, by analyzing the distribution of potential prognostic factors in CLL patients, we displayed a landscape of molecular profiles, confirmed the predictive value of recurrent genetic mutations and chromosome aberrations, and found that IGHJ3 was associated with favorable markers (mutated IGHV, trisomy 12), while IGHJ6 tended to correlate with unfavorable factors (unmutated IGHV, del17p).

Discussion

These results provided an indication for IGH gene sequencing in predicting the prognosis of CLL.

Extracellular Vesicles in Diffuse Large B Cell Lymphoma: Characterization and Diagnostic Potential

Diffuse large B cell lymphoma (DLBCL) is an aggressive B cell lymphoma characterized by a heterogeneous behavior and in need of more accurate biological characterization monitoring and prognostic tools. Extracellular vesicles are secreted by all cell types and are currently established to some extent as representatives of the cell of origin. The present study characterized and evaluated the diagnostic and prognostic potential of plasma extracellular vesicles (EVs) proteome in DLBCL by using state-of-the-art mass spectrometry. The EV proteome is strongly affected by DLBCL status, with multiple proteins uniquely identified in the plasma of DLBCL. A proof-of-concept classifier resulted in highly accurate classification with a sensitivity and specificity of 1 when tested on the holdout test data set. On the other hand, no proteins were identified to correlate with non-germinal center B-cell like (non-GCB) or GCB subtypes to a significant degree after correction for multiple testing. However, functional analysis suggested that antigen binding is regulated when comparing non-GCB and GCB. Survival analysis based on protein quantitative values and clinical parameters identified multiple EV proteins as significantly correlated to survival. In conclusion, the plasma extracellular vesicle proteome identifies DLBCL cancer patients from healthy donors and contains potential EV protein markers for prediction of survival.

AQP9 Is a Prognostic Factor for Kidney Cancer and a Promising Indicator for M2 TAM Polarization and CD8+ T-Cell Recruitment

Background

It is undeniable that the tumor microenvironment (TME) plays an indispensable role in the progression of kidney renal clear cell carcinoma (KIRC). However, the precise mechanism of activities in TME is still unclear.

Methods and Results

Using the CIBERSORT and ESTIMATE calculation methods, the scores of the two main fractions of tumor-infiltrating immune cells (TICs) from The Cancer Genome Atlas (TCGA) database of 537 KIRC patients were calculated. Subsequently, differentially expressed genes (DEGs) were drawn out by performing an overlap between Cox regression analysis and protein–protein interaction (PPI) network. Aquaporin 9 (AQP9) was identified as a latent predictor through the process. Following research revealed that AQP9 expression was positively correlated with the pathological characteristics (TNM stage) and negatively connected with survival time. Then, by performing gene set enrichment analysis (GSEA), it can be inferred that genes with high expression level of AQP9 were mainly enriched in immune-related activities, while low AQP9 group was associated with functions of cellular metabolism. Further studies have shown that regulatory T cells (Tregs), macrophages M2, macrophages M0, CD4+ T cells, and neutrophils were positively correlated with AQP9 expression. While the levels of mast cells, natural killer (NK) cells, and CD8+ T cells are negatively correlated with AQP9. The result of multiple immunohistochemistry (mIHC) suggests a negative relevance between AQP9 and CD8+ T cells and reveals a trend of consistent change on AQP9 and M2 macrophages.

Conclusion

The expression level of AQP9 may be helpful in predicting the prognosis of patients with KIRC, especially to the TME state transition, the mechanism of which is possibly through lipid metabolism and P53, Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathways that affect M2 polarization. AQP9 was associated with the expression levels of M2, tumor-associated macrophages (TAMs), and the recruitment of CD8+ T cells in tumor environment. The research result indicates that AQP9 may be an obstacle to maintain the immune activity of TME.

A Personalized Genomics Approach of the Prostate Cancer

Decades of research identified genomic similarities among prostate cancer patients and proposed general solutions for diagnostic and treatments. However, each human is a dynamic unique with never repeatable transcriptomic topology and no gene therapy is good for everybody. Therefore, we propose the Genomic Fabric Paradigm (GFP) as a personalized alternative to the biomarkers approach. Here, GFP is applied to three (one primary—“A”, and two secondary—“B” & “C”) cancer nodules and the surrounding normal tissue (“N”) from a surgically removed prostate tumor. GFP proved for the first time that, in addition to the expression levels, cancer alters also the cellular control of the gene expression fluctuations and remodels their networking. Substantial differences among the profiled regions were found in the pathways of P53-signaling, apoptosis, prostate cancer, block of differentiation, evading apoptosis, immortality, insensitivity to anti-growth signals, proliferation, resistance to chemotherapy, and sustained angiogenesis. ENTPD2, AP5M1 BAIAP2L1, and TOR1A were identified as the master regulators of the “A”, “B”, “C”, and “N” regions, and potential consequences of ENTPD2 manipulation were analyzed. The study shows that GFP can fully characterize the transcriptomic complexity of a heterogeneous prostate tumor and identify the most influential genes in each cancer nodule.