Journal of Experimental & Clinical Cancer Research最新文献

Background: In non-small cell lung cancer (NSCLC), the rapid advancement of predictive genetic testing of tumors by identifying specific pathogenic driver variants has significantly improved treatment guidance. However, immune checkpoint blockade (ICB) is typically administered to patients with tumors in the absence of such driver variants. Since only about 30% of patients will respond to ICB treatment, identifying novel genetic biomarkers of clinical response is crucial and will improve treatment decisions. This prospective clinical study aims to combine molecular biology, advanced bioinformatics and clinical data on response to treatment with ICB from a prospective cohort of NSCLC patients to identify single or combination of genetic variants in the tumor that can serve as predictive biomarkers of clinical response.

Methods: In this prospective bi-center clinical study, we performed next-generation sequencing (NGS) of 597 cancer-associated genes in a prospective cohort of 49 patients as the final cohort analyzed, with stage III or IV NSCLC, followed by establishment of an in-house developed bioinformatics-based molecular classification method that integrates, interprets and evaluates data from multiple databases and variant prediction tools. Overall survival (OS) and progression-free survival (PFS) were analyzed for selected candidate genes and variants identified using our novel methodology including molecular tools, databases and clinical information.

Results: Our novel molecular interpretation and classification method identified high impact variants in frequently altered genes KRAS, LRP1B, and TP53. Analysis of these genes as single predictive biomarkers in ICB-treated patients revealed that the presence of likely pathogenic variants and variants of unclear significance in LRP1B was associated with improved OS (p = 0.041). Importantly, further analysis of variant combinations in the tumor showed that co-occurrence of KRAS and LRP1B variants significantly improved OS (p = 0.003) and merged PFS (p = 0.008). Notably, the triple combination of variants in KRAS, LRP1B, and TP53 positively impacted both OS (p = 0.026) and merged PFS (p = 0.003).

Conclusions: This study suggests that combination of the LRP1B and KRAS variants identified through our novel molecular classification scheme leads to better outcomes following ICB treatment in NSCLC. The addition of TP53 improves the outcome even further. To our knowledge, this is the first report indicating that harboring a combination of KRAS, LRP1B, and TP53 variants can significantly enhance the response to ICB, suggesting a novel predictive biomarker combination for NSCLC patients.

Background: Tumor resistance represents a major challenge in the current oncology landscape. Asparagine endopeptidase (AEP) overexpression correlates with worse prognosis and reduced overall survival in most human solid tumors. However, the underlying mechanisms of the connection between AEP and reduced overall survival in cancer patients remain unclear.

Methods: High-throughput proteomics, cellular and molecular biology approaches and clinical data from breast cancer (BC) patients were used to identify novel, biologically relevant AEP targets. Immunoblotting and qPCR analyses were used to quantify protein and mRNA levels. Flow cytometry, confocal microscopy, chemical inhibitors, siRNA- and shRNA-silencing and DNA repair assays were used as functional assays. In-silico analyses using the TCGA BC dataset and immunofluorescence assays in an independent cohort of invasive ductal (ID) BC patients were used to validate the clinical relevance of our findings.

Results: Here we showed a dual role for AEP in genomic stability and radiotherapy resistance in BC patients by suppressing ATR and PPP1R10 levels. Reduced ATR and PPP1R10 levels were found in BC patients expressing high AEP levels and correlated with worst prognosis. Mechanistically, AEP suppresses ATR levels, reducing DNA damage-induced cell death, and PPP1R10 levels, promoting Chek1/P53 cell cycle checkpoint activation, allowing BC cells to efficiently repair DNA. Functional studies revealed AEP-deficiency results in genomic instability, increased DNA damage signaling, reduced Chek1/P53 activation, impaired DNA repair and cell death, with phosphatase inhibitors restoring the DNA damage response in AEP-deficient BC cells. Furthermore, AEP inhibition sensitized BC cells to the chemotherapeutic reagents cisplatin and etoposide. Immunofluorescence assays in an independent cohort of IDBC patients showed increased AEP levels in ductal cells. These analyses showed that higher AEP levels in radioresistant IDBC patients resulted in ATR nuclear eviction, revealing AEPhigh/ATRlow protein levels as an efficient predictive biomarker for the stratification of radioresistant patients.

Conclusion: The newly identified AEP/ATR/PPP1R10 axis plays a dual role in genomic stability and radiotherapy resistance in BC. Our work provides new clues to the underlying mechanisms of tumor resistance and strong evidence validating the AEP/ATR axis as a novel predictive biomarker and therapeutic target for the stratification and treatment of radioresistant BC patients.

Background: The emergence of targeted therapies and immunotherapy has broadened treatment options for patients with pancreatic ductal adenocarcinoma (PDAC). Despite this, traditional drug selection, predominantly relies on tumor markers and clinical staging, has underutilized these drugs due to ignoring patient genomic diversity. Patient-derived organoids (PDOs) and corresponding patient-derived organoid xenograft (PDOX) models offer a way to better understand and address this.

Methods: In this study, we established PDOs and PDOX models from PDAC clinical samples. These models were analyzed using immunohistochemistry, H&E staining, and genomic profiling. Drug screening with 111 FDA-approved drugs was performed on PDOs, and drug responses in PDOs and PDOX models were compared to assess consistency with clinical treatment outcomes. Gene analysis was conducted to explore the molecular mechanisms underlying variations in drug responses. Additionally, by analyzing the sequencing results from various drug-sensitive groups, the identified differential gene-drug metabolism gene UGT1A10 were modulated in PDOs to evaluate its impact on drug efficacy. A co-culture system of PDOs with immune cells was developed to study the efficacy of immunotherapies.

Results: PDOs and matched PDOX models retain the morphological, biological, and genomic characteristics of the primary tumor. Exome sequencing and RNA sequencing confirmed both the consistency and heterogeneity among the PDOs. High-throughput drug screening revealed significant variability in drug sensitivity across different organoids, yet PDOs and PDOX derived from the same patient exhibited a high degree of concordance in response to clinical chemotherapy agents. The gene expression analysis of PDOs with significant differences in drug sensitivity revealed UGT1A10 as a crucial regulator. The knockdown of UGT1A10 notably increased drug sensitivity. Furthermore, immune cells demonstrated specific cytotoxicity towards the organoids, underscoring the potential of the co-culture system for application in tumor immunotherapy.

Conclusion: Our results highlight the necessity for personalized treatment strategies that consider genomic diversity beyond tumor markers, thus validating the utility of PDOs and PDOX models in advancing PDAC research and personalized medicine.

Background: Mutations in KRAS and BRAF genes are prevalent in colorectal cancer (CRC), which strikingly promote tumorigenesis and lead to poor response to a variety of treatments including immunotherapy by activating the MAPK/ERK pathway. Thus, there is an urgent need to discover effective therapeutic targets and strategies.

Methods: CRISPR-Cas9 lentiviral knockout library was used to screen the suppressors of anti-PD1 immunotherapy. Bioinformatic analysis was used to analyze the correlation between PHF8 expression and immune indicators in CRC. In vitro and in vivo experiments were utilized to determine the effects of PHF8 on the immune indexes and malignant phenotypes of CRC cells. qRT-PCR, western blotting, immunohistochemical (IHC) staining, and chromatin immunoprecipitation (ChIP)-qPCR assays were used to determine the regulatory effects of PHF8 on PD-L1, KRAS, BRAF, and c-Myc and the regulatory effect c-Myc/miR-22-3p signaling axis on PHF8 expression in CRC cells.

Results: This study identified histone lysine demethylase PHF8 as a negative regulator for the efficacy of anti-PD1 therapy and found that it was highly expressed in CRCs and strongly associated with poor patient survival. Functional studies showed that PHF8 played an oncogenic role in KRAS- or BRAF-mutant CRC cells, but not in wild-type ones. Mechanistically, PHF8 up-regulated the expression of PD-L1, KRAS, BRAF, and c-Myc by increasing the levels of transcriptional activation marks H3K4me3 and H3K27ac and decreasing the levels of transcriptional repression mark H3K9me2 within their promoter regions, promoting immune escape and tumor progression. Besides, our data also demonstrated that PHF8 was up-regulated by the c-Myc/miR-22-3p signaling axis to form a positive feedback loop. Targeting PHF8 substantially improved the efficacy of anti-PD1 therapy and inhibited the malignant phenotypes of KRAS- or BRAF-mutant CRC cells.

Conclusion: Our data demonstrate that PHF8 may be an effective therapeutic target for KRAS- or BRAF-mutant CRCs.

Backgroud: Sustaining proliferation signaling is the top hallmarks of cancer, driving continuous tumor growth and resistance to drug treatments. Blocking proliferation signaling has shown limited benefit in clinical treatment of pancreatic ductal adenocarcinoma, highlighting the urgent need to deeply understand proliferation signaling and develop new therapeutic strategies.

Methods: By leveraging clinical data and data from the TCGA and GDSC datasets, we investigated the association between MMP-28 expression and the sensitivity to EGFR inhibitors as well as the prognosis of PDAC. Transcriptomic and biological experiments explore the regulatory role of MMP-28 on the EGFR signaling pathway. Additionally, in vitro and in vivo studies are employed to evaluate MMP-28 as a biomarker for sensitivity to EGFR inhibitors.

Results: We found that MMP-28, a metalloproteinase, was significantly associated with the sensitivity to EGFR inhibitors. Furthermore, MMP-28 could promote PDAC growth and metastasis. Mechanistically, MMP-28 facilitated the maturation and release of the TGF-α precursor, thus promoting EGFR activation. In return, EGFR upregulated MMP-28 through AP-1-mediated transcription, forming a positive feedback loop that provided sustaining proliferation signaling for PDAC. Subsequently, MMP-28 was identified to predict the response to EGFR inhibitors and recognize responsive patients.

Conclusions: Our findings revealed the role of MMP-28 and EGFR in generation of sustaining proliferation signaling and provided a new therapy strategy for PDAC.