Association of immune checkpoint inhibitor with survival in patients with cancers with protein tyrosine phosphatase receptor T mutation

PTPRT loss enhances anti-PD-1 therapy efficacy by regulation of STING pathway in non-small cell lung cancer

With the revolutionary progress of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer, identifying patients with cancer who would benefit from ICIs has become critical and urgent. Here, we report protein tyrosine phosphatase receptor type T (PTPRT) loss as a precise and convenient predictive marker independent of PD-L1 expression for anti-PD-1/PD-L1 axis therapy. Anti-PD-1/PD-L1 axis treatment markedly increased progression-free survival in patients with PTPRT-deficient tumors. PTPRT-deficient tumors displayed cumulative DNA damage, increased cytosolic DNA release, and higher tumor mutation burden. Moreover, the tyrosine residue 240 of STING was identified as a direct substrate of PTPRT. PTPRT loss elevated phosphorylation of STING at Y240 and thus inhibited its proteasome-mediated degradation. PTPRT-deficient tumors released more IFN-β, CCL5, and CXCL10 by activation of STING pathway and increased immune cell infiltration, especially of CD8 T cells and natural killer cells, ultimately enhancing the efficacy of anti-PD-1 therapy in multiple subcutaneous and orthotopic tumor mouse models. The response of PTPRT-deficient tumors to anti-PD-1 therapy depends on the tumor-intrinsic STING pathway. In summary, our findings reveal the mechanism of how PTPRT-deficient tumors become sensitive to anti-PD-1 therapy and highlight the biological function of PTPRT in innate immunity. Considering the prevalence of PTPRT mutations and negative expression, this study has great value for patient stratification and clinical decision-making.

Deciphering the role of apoptosis signature on the immune dynamics and therapeutic prognosis in breast cancer: Implication for immunotherapy

Background: In breast cancer oncogenesis, the precise role of cell apoptosis holds untapped potential for prognostic and therapeutic insights. Thus, it is important to develop a model predicated for breast cancer patients' prognosis and immunotherapy response based on apoptosis-related signature. Methods: Our approach involved leveraging a training dataset from The Cancer Genome Atlas (TCGA) to construct an apoptosis-related gene prognostic model. The model's validity was then tested across several cohorts, including METABRIC, Sun Yat-sen Memorial Hospital Sun Yat-sen University (SYSMH), and IMvigor210, to ensure its applicability and robustness across different patient demographics and treatment scenarios. Furthermore, we utilized Quantitative Polymerase Chain Reaction (qPCR) analysis to explore the expression patterns of these model genes in breast cancer cell lines compared to immortalized mammary epithelial cell lines, aiming to confirm their differential expression and underline their significance in the context of breast cancer. Results: Through the development and validation of our prognostic model based on seven apoptosis-related genes, we have demonstrated its substantial predictive power for the survival outcomes of breast cancer patients. The model effectively stratified patients into high and low-risk categories, with high-risk patients showing significantly poorer overall survival in the training cohort and across all validation cohorts. Importantly, qPCR analysis confirmed that the genes constituting our model indeed exhibit differential expression in breast cancer cell lines when contrasted with immortalized mammary epithelial cell lines. Conclusion: Our study establishes a groundbreaking prognostic model using apoptosis-related genes to enhance the precision of breast cancer prognosis and treatment, particularly in predicting immunotherapy response.

Downregulation of PTPRT elevates the expression of survivin and promotes the proliferation, migration, and invasion of lung adenocarcinoma

BACKGROUND

Receptor-type tyrosine-protein phosphatase T (PTPRT) is a transmembrane protein that is involved in cell adhesion. We previously found that PTPRT was downregulated in multiple cancer types and the mutation of PTPRT was associated with cancer early metastasis. However, the impacts of PTPRT downregulation on tumour proliferation, invasion, and clinical interventions such as immune checkpoint inhibitor (ICI) therapies remained largely unknown.

METHODS

Gene expression data of non-small cell lung cancer (NSCLC) samples from The Cancer Genome Atlas database were downloaded and used to detect the differential expressed genes between PTPRT-high and PTPRT-low subgroups. Knockdown and overexpress of PTPRT in lung cancer cell lines were performed to explore the function of PTPRT in vitro. Western blot and qRT-PCR were used to evaluate the expression of cell cycle-related genes. CCK-8 assays, wound-healing migration assay, transwell assay, and colony formation assay were performed to determine the functional impacts of PTPRT on cell proliferation, migration, and invasion. KM-plotter was used to explore the significance of selected genes on patient prognosis.

RESULTS

PTPRT was found to be downregulated in tumours and lung cancer cell lines compared to normal samples. Cell cycle-related genes (BIRC5, OIP5, and CDCA3, etc.) were specifically upregulated in PTPRT-low lung adenocarcinoma (LUAD). Modulation of PTPRT expression in LUAD cell lines affected the expression of BIRC5 (survivin) significantly, as well as the proliferation, migration, and invasion of tumour cells. In addition, low PTPRT expression level was correlated with worse prognosis of lung cancer and several other cancer types. Furthermore, PTPRT downregulation was associated with elevated tumour mutation burden and tumour neoantigen burden in lung cancer, indicating the potential influence on tumour immunogenicity.

CONCLUSION

Our findings uncovered the essential roles of PTPRT in the regulation of proliferation, migration, and invasion of LUAD, and highlighted the clinical significance of PTPRT downregulation in lung cancer.

A Comprehensive Analysis of Programmed Cell Death-Associated Genes for Tumor Microenvironment Evaluation Promotes Precise Immunotherapy in Patients with Lung Adenocarcinoma

Immune checkpoint inhibitors (ICIs) represent a new hot spot in tumor therapy. Programmed cell death has an important role in the prognosis. We explore a programmed cell death gene prognostic model associated with survival and immunotherapy prediction via computational algorithms. Patient details were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. We used LASSO algorithm and multiple-cox regression to establish a programmed cell death-associated gene prognostic model. Further, we explored whether this model could evaluate the sensitivity of patients to anti-PD-1/PD-L1. In total, 1342 patients were included. We constructed a programmed cell death model in TCGA cohorts, and the overall survival (OS) was significantly different between the high- and low-risk score groups (HR 2.70; 95% CI 1.94–3.75; p < 0.0001; 3-year OS AUC 0.71). Specifically, this model was associated with immunotherapy progression-free survival benefit in the validation cohort (HR 2.42; 95% CI 1.59–3.68; p = 0.015; 12-month AUC 0.87). We suggest that the programmed cell death model could provide guidance for immunotherapy in LUAD patients.

Association of PTPRT Mutations with Cancer Metastasis in Multiple Cancer Types

Metastasis is one of the characteristics of advanced cancer and the primary cause of cancer-related deaths from cancer, but the mechanism underlying metastasis is unclear, and there is a lack of metastasis markers. PTPRT is a protein-coding gene involved in both signal transduction and cellular adhesion. It is also known as a tumor suppressor gene that inhibits cell malignant proliferation by inhibiting the STAT3 pathway. Recent studies have reported that PTPRT is involved in the early metastatic seeding of colorectal cancer; however, the correlation between PTPRT and metastasis in other types of cancer has not been revealed. A combined analysis using a dataset from the genomics evidence neoplasia information exchange (GENIE) and cBioPortal revealed that PTPRT mutation is associated with poor prognosis in pan-cancer and non-small-cell lung cancer. The mutations of PTPRT or “gene modules” containing PTPRT are significantly enriched in patients with metastatic cancer in multiple cancers, suggesting that the PTPRT mutations serve as potential biomarkers of cancer metastasis.

Anchored Multiplex PCR Custom Melanoma Next Generation Sequencing Panel for Analysis of Circulating Tumor DNA

Detection of melanoma mutations using circulating tumor DNA (ctDNA) is a potential alternative to using genomic DNA from invasive tissue biopsies. To date, mutations in the GC-rich TERT promoter region, which is commonly mutated in melanoma, have been technically difficult to detect in ctDNA using next-generation sequencing (NGS) panels. In this study, we developed a custom melanoma NGS panel for detection of ctDNA, which encompasses the top 15 gene mutations in melanoma including the TERT promoter. We analyzed 21 stage III and IV melanoma patient samples who were treatment-naïve or on therapy. The overall detection rate of the custom panel, based on BRAF/NRAS/TERT promoter mutations, was 14/21 (67%) patient samples which included a TERT C250T mutation in one BRAF and NRAS mutation negative sample. A BRAF or NRAS mutation was detected in the ctDNA of 13/21 (62%) patients while TERT promoter mutations were detected in 10/21 (48%) patients. Co-occurrence of TERT promoter mutations with BRAF or NRAS mutations was found in 9/10 (90%) patients. The custom ctDNA panel showed a concordance of 16/21 (76%) with tissue based-detection and included 12 BRAF/NRAS mutation positive and 4 BRAF/NRAS mutation negative patients. The ctDNA mutation detection rate for stage IV was 12/16 (75%) and for stage III was 1/5 (20%). Based on BRAF, NRAS and TERT promoter mutations, the custom melanoma panel displayed a limit of detection of ~0.2% mutant allele frequency and showed significant correlation with droplet digital PCR. For one patient, a novel MAP2K1 H119Y mutation was detected in an NRAS/BRAF/TERT promoter mutation negative background. To increase the detection rate to >90% for stage IV melanoma patients, we plan to expand our custom panel to 50 genes. This study represents one of the first to successfully detect TERT promoter mutations in ctDNA from cutaneous melanoma patients using a targeted NGS panel.

Neoadjuvant camrelizumab, nab-paclitaxel, and carboplatin in patients with stage IB-IIIA non-small cell lung cancer (NANE-LC): a study protocol of prospective, single-arm, multicenter, phase II study

Background

Previous studies have shown that neoadjuvant immune checkpoint inhibitors (ICIs) combined with chemotherapy in patients with stage IB–IIIA non-small cell lung cancer (NSCLC) significantly improved the major pathological response (MPR) and the pathological complete response (pCR) rates. However, high-level evidence-based medical data confirming this effect are still lacking. In addition, there is an urgent need to develop an appropriate strategy to predict the benefit for patients receiving ICIs. In this study, we describe an ongoing study on the effect of neoadjuvant therapy with camrelizumab, nab-paclitaxel, and carboplatin on stage IB–IIIA NSCLC patients. The aim of this study is to establish a multiomics artificial intelligence system for predicting neoadjuvant therapy efficacy and assisting decision-making.

Methods

This prospective, single-arm, multicenter, phase II trial will enroll a total of 40 patients who will undergo surgery after three cycles of neoadjuvant therapy with camrelizumab, nab-paclitaxel, and carboplatin. The MPR rate is the primary endpoint, while the rates of pCR, complete resection, objective response, disease-free survival (DFS), adverse events (AEs), and quality of life (QOL) are secondary endpoints. Exploratory endpoints will serve to establish a multiomics artificial intelligence system for neoadjuvant therapy effect prediction and decision-making assistance based on radiomics, metabolism, genetic, and clinic-pathological characteristics and to explore the mechanisms of drug resistance.

Discussion

The efficacy of ICIs is influenced by many factors, including patient’s driver genes and smoking status. Thus, further subgroup analysis is needed. This study will indicate if our new multiomics artificial intelligence system constitutes a valid strategy for neoadjuvant therapy effect prediction and decision-making assistance in the context of neoadjuvant camrelizumab, nab-paclitaxel, and carboplatin treatment for patients with stage IB–IIIA NSCLC.

Trial Registration

This trial has been registered at ClinicalTrials.gov (identification number: NCT04541251).

Association of PTPRT mutations with immune checkpoint inhibitors response and outcome in melanoma and non-small cell lung cancer

Purpose

Protein tyrosine phosphatase receptor type T (PTPRT), which is a well‐known phosphatase and mutates frequently in melanoma and non‐small cell lung cancer (NSCLC). Our research aims to elucidate its mutation association with immune checkpoint inhibitors (ICI) efficacy.

Methods

We integrated whole‐exome sequencing (WES)‐based somatic mutation profiles and clinical characteristics of 631 melanoma samples received ICI agents from eight studies and 109 NSCLC samples from two studies. For validation, 321 melanoma and 350 NSCLC immunotherapy samples with targeted next‐generation sequencing (NGS) were employed. Besides, an independent NSCLC cohort contained 240 samples was also collected for further corroboration. Distinct immune infiltration was evaluated according to the PTPRT mutational status.

Results

In the WES melanoma cohort, patients with PTPRT mutations harbored a significantly elevated ICI response rate (40.5% vs. 28.6%, p = 0.036) and a prolonged survival outcome (35.3 vs. 24.9 months, p = 0.006). In the WES NSCLC cohort, the favorable response and immunotherapy survival were also observed in PTPRT‐mutated patients (p = 0.036 and 0.019, respectively). For the validation cohorts, the associations of PTRPT mutations with better prognoses were identified in melanoma, NSCLC, and pan‐cancer patients with targeted‐NGS (all p < 0.05). Moreover, immunology analyses showed the higher mutation burden, increased lymphocyte infiltration, decreased‐ activated‐stroma, and immune response pathways were detected in patients with PTPRT mutations.

Conclusion

Our investigation indicates that PTPRT mutations may be considered as a potential indicator for assessing ICI efficacy in melanoma and NSCLC, even across multiple cancers. Further prospective validation cohorts are warranted.