LRP1B is a Potential Biomarker for Tumor Immunogenicity and Prognosis of HCC Patients Receiving ICI Treatment

Using a Dual CRISPR/Cas9 Approach to Gain Insight into the Role of LRP1B in Glioblastoma

LRP1B remains one of the most altered genes in cancer, although its relevance in cancer biology is still unclear. Recent advances in gene editing techniques, particularly CRISPR/Cas9 systems, offer new opportunities to evaluate the function of large genes, such as LRP1B. Using a dual sgRNA CRISPR/Cas9 gene editing approach, this study aimed to assess the impact of disrupting LRP1B in glioblastoma cell biology. Four sgRNAs were designed for the dual targeting of two LRP1B exons (1 and 85). The U87 glioblastoma (GB) cell line was transfected with CRISPR/Cas9 PX459 vectors. To assess LRP1B-gene-induced alterations and expression, PCR, Sanger DNA sequencing, and qRT-PCR were carried out. Three clones (clones B9, E6, and H7) were further evaluated. All clones presented altered cellular morphology, increased cellular and nuclear size, and changes in ploidy. Two clones (E6 and H7) showed a significant decrease in cell growth, both in vitro and in the in vivo CAM assay. Proteomic analysis of the clones' secretome identified differentially expressed proteins that had not been previously associated with LRP1B alterations. This study demonstrates that the dual sgRNA CRISPR/Cas9 strategy can effectively edit LRP1B in GB cells, providing new insights into the impact of LRP1B deletions in GBM biology.

Necroptosis-related signatures identify two distinct hepatocellular carcinoma subtypes: Implications for predicting drug sensitivity and prognosis

Background

Necroptosis is associated with oncogenesis, tumor immunity and progression. This research aims to investigate the association of necroptosis-related genes with drug sensitivity and prognosis in hepatocellular carcinoma (HCC).

Methods

Based on necroptosis-related signatures, HCC patients retrieved from the TCGA database were categorized. Survival outcomes, mutation profile, immune microenvironment, and drug sensitivity between HCC subtypes were further compared. Then, LASSO analysis was performed to construct a necroptosis-related prognostic signature, which was further evaluated using another independent cohort.

Results

A total of 371 patients with HCC could be categorized into two necroptosis-related subtypes. About 36% of patients were allocated to subtype A, with worse survival, more mutant TP53, and a lower likelihood of immunotherapy response. In contrast, patients in subtype B had a favorable prognosis, with lower expression of immunosuppressive signatures but a lower abundance of B and CD8⁺ T-cell infiltration. The prognostic risk score calculated using the expression levels of nine genes involved in the necroptosis pathway (MLKL, FADD, XIAP, USP22, UHRF1, CASP8, RIPK3, ZBP1, and FAS) showed a significant association with tumor stage, histologic grade, and Child‒Pugh score. Additionally, the risk score model was proven to be accurate in both the training and independent external validation cohorts and performed better than the TNM staging system and three well-recognized risk score models.

Conclusions

Based on necroptosis-related signatures, we identified two HCC subtypes with distinctive immune microenvironments, mutation profiles, drug sensitivities, and survival outcomes. A novel well-performing prognostic model was further constructed.

Prognostic biomarkers correlated with immune infiltration in non-small cell lung cancer

Lung cancer is the leading cause of cancer-related mortality in men and women globally. Non-small cell lung cancer (NSCLC) is the most prevalent subtype, accounting for 85-90% of all cancers. Although there have been dramatic advances in therapeutic approaches in recent decades, the recurrence and metastasis rates of NSCLC are as high as 30-40% with the 5-year overall survival rate being less than 15%. Therefore, it is necessary to explore the pathogenesis of NSCLC at the genetic level and identify prognostic biomarkers and novel therapeutic targets. Here, we aimed to identify mutated genes with high frequencies in Chinese NSCLC patients using next-generation sequencing and to investigate their relationships with the tumor mutation burden (TMB) and tumor immune microenvironment. A total of 110 NSCLC patients were enrolled to profile the genetic variations. Mutations in EGFR (62.37%), TP53 (61.29%), LRP1B (13.98%), FAT1 (12.90%), KMT2D (11.83%), CREBBP (10.75%), and RB1 (9.68%) were most prevalent. TP53, LRP1B, KMT2D, and CREBBP mutations were all significantly associated with high TMB (P < 0.05 or P < 0.01). The infiltrating levels of immune cells and immune molecules were enriched significantly in the LRP1B mutation group. LRP1B mutations significantly correlated with stimulating and inhibitory immunoregulators. Gene set enrichment analysis revealed that cell cycle, the Notch signaling pathway, the insulin signaling pathway, and the mTOR signaling pathway are related to LRP1B mutations in the immune system. LRP1B mutations may be of clinical importance in enhancing the anti-tumor immune response and may be a promising biomarker for predicting immunotherapy responsiveness.

Analysis of copy number alterations in bladder cancer stem cells revealed a prognostic role of LRP1B

Purpose

Bladder cancer is the most common malignancy of the urinary tract and one of the most prevalent cancers worldwide. It represents a spectrum of diseases, from recurrent non-invasive tumors (NMIBCs) managed chronically, to muscle infiltrating and advanced-stage disease (MIBC) that requires multimodal and invasive treatment. Multiple studies have underlined the complexity of bladder tumors genome, highlighting many specific genetic lesions and genome-wide occurrences of copy-number alterations (CNAs). In this study, we analyzed CNAs of selected genes in our cohorts of cancer stem cells (CSCs) and in The Cancer Genome Atlas (TCGA-BLCA) cohort with the aim to correlate their frequency with patients’ prognosis.

Methods

CNAs have been verified on our array-CGH data previously reported on 19 bladder cancer biopsies (10 NMIBCs and 9 MIBCs) and 16 matched isolated CSC cultures. In addition, CNAs data have been consulted on the TCGA database, to search correlations with patients’ follow-up. Finally, mRNA expression levels of LRP1B in TGCA cohort were obtained from The Human Protein Atlas.

Results

We firstly identified CNAs differentially represented between TGCA data and CSCs derived from NMIBCs and MIBCs, and we correlated the presence of these CNAs with patients’ follow-up. LRP1B loss was significantly increased in CSCs and linked to short-term poor prognosis, both at genomic and transcriptomic level, confirming its pivotal role in bladder cancer tumorigenesis.

Conclusion

Our study allowed us to identify potential "predictive" prognostic CNAs for bladder cancer, implementing knowledge for the ultimate goal of personalized medicine.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00345-022-04093-1.

LRP1B mutation associates with increased tumor mutation burden and inferior prognosis in liver hepatocellular carcinoma

BACKGROUND

Liver hepatocellular carcinoma (LIHC) is the most common primary liver cancer and the main cause of death in patients with cirrhosis. LRP1B is found to involve in a variety of cancers, but the association of LRP1B mutation with tumor mutation burden (TMB) and prognosis of LIHC is rarely studied.

METHODS AND RESULTS

Herein, we analyzed the somatic mutation data of 364 LIHC patients from The Cancer Genome Atlas (TCGA) and found that LRP1B showed elevated mutation rate. Calculation of the TMB in LRP1B mutant and LRP1B wild-type groups showed that LRP1B mutant group had higher TMB compared with that in LRP1B wild-type group. Then survival analysis was performed and the survival curve showed that LRP1B mutation was associated with poor survival outcome, and this association remained to be significant after adjusting for multiple confounding factors including age, gender, tumor stage, mutations of BRCA1, BRCA2, and POLE.

CONCLUSION

Collectively, our results revealed that LRP1B mutation was related to high TMB value and poor prognosis in LIHC, indicating that LRP1B mutation is probably helpful for the selection of immunotherapy and prognosis prediction in LIHC.