PTPRT Could Be a Treatment Predictive and Prognostic Biomarker for Breast Cancer

Targeting Neoantigens in Cancer: Possibilities and Opportunities in Breast Cancer

As one of the most prevalent forms of cancer worldwide, breast cancer has garnered significant attention within the clinical research setting. While traditional treatment employs a multidisciplinary approach including a variety of therapies such as chemotherapy, hormone therapy, and even surgery, researchers have since directed their attention to the budding role of neoantigens. Neoantigens are defined as tumor-specific antigens that result from a multitude of genetic alterations, the most prevalent of which is the single nucleotide variant. As a result of their foreign nature, neoantigens elicit immune responses upon presentation by Major Histocompatibility Complexes I and II followed by recognition by T cell receptors. Previously, researchers have been able to utilize these immunogenic properties and manufacture neoantigen-specific T-cells and neoantigen vaccines. Within the context of breast cancer, biomarkers such as tumor protein 53 (TP53), Survivin, Partner and Localizer of BRCA2 (PALB2), and protein tyrosine phosphatase receptor T (PTPRT) display exceeding potential to serve as neoantigens. However, despite their seemingly limitless potential, neoantigens must overcome various obstacles if they are to be fairly distributed to patients. For instance, a prolonged period between the identification of a neoantigen and the dispersal of treatment poses a serious risk within the context of breast cancer. Regardless of these current obstacles, it appears highly promising that future research into neoantigens will make an everlasting impact on the health outcomes within the realm of breast cancer. The purpose of this literature review is to comprehensively discuss the etiology of various forms of breast cancer and current treatment modalities followed by the significance of neoantigens in cancer therapeutics and their application to breast cancer. Further, we have discussed the limitations, future directions, and the role of transcriptomics in neoantigen identification and personalized medicine. The concepts discussed in the original and review articles were included in this review article.

PTPRD/PTPRT mutation as a predictive biomarker of immune checkpoint inhibitors across multiple cancer types

Background

Immune checkpoint inhibitors (ICIs) are dramatically changing the treatment landscape of a variety of cancers. Nevertheless, the variability in ICI responses highlight the importance in identifying predictive biomarkers. PTPRD and PTPRT (PTPRD/PTPRT) are the phosphatases of JAK-STAT signaling, a critical pathway in anti-cancer immunity regulation. However, the pan-cancer association between PTPRD/PTPRT mutation and the efficacy of ICIs remains unclear across pan-cancer patients.

Methods

We analyzed the association between PTPRD/PTPRT mutations and patient outcomes using clinical data and genomic mutations from TCGA pan-cancer cohort. Furthermore, the ICI-treatment cohort was used to evaluate the relationship between PTPRD/PTPRT mutation and the efficacy of ICIs. Another ICIs-treatment cohort was used to validate the findings. The TCGA pan-cancer dataset was analyzed to explore the correlation between PTPRD/PTPRT mutations and immune signatures. Moreover, we combined four factors to construct a nomogram model that could be used to predict the survival of pan-cancer patients receiving ICI treatment. The calibration curves and area under the curve were applied to assess the performance of the model.

Results

PTPRD/PTPRT mutations were shown to be associated with a worse prognosis in TCGA cohort (P < 0.05). In the Samstein cohort, prolonged overall survival (OS) was observed in PTPRD/PTPRT mutant cancers, compared with wild-type cancers (mOS: 40.00 vs 16.00 months, HR = 0.570, 95%CI: 0.479-0.679, P < 0.0001). In the validation cohort, significant OS advantage was observed in PTPRD/PTPRT mutant patients (mOS: 31.32 vs 15.53 months, HR = 0.658, 95%CI: 0.464-0.934, P = 0.0292). Furthermore, PTPRD/PTPRT mutations were associated with a higher tumor mutational burden, MSI score, and TCR score (P < 0.0001). Enhanced immune signatures were found in the PTPRD/PTPRT mutant cancers (P < 0.05). Finally, we successfully established a nomogram model that could be used to predict the survival of NSCLC patients who received ICI treatment. Based on the risk score of the model, patients in the low-risk group showed a better mOS than those in the high-risk group (mOS: 2.75 vs 1.08 years, HR = 0.567, 95%CI: 0.492-0.654; P < 0.001).

Conclusions

PTPRD/PTPRT mutations may be a potential biomarker for predicting ICI treatment responsiveness in multiple cancer types.

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.

An Eleven-microRNA Signature Related to Tumor-Associated Macrophages Predicts Prognosis of Breast Cancer

The dysregulation of microRNAs (miRNAs) has been known to play important roles in tumor development and progression. However, the understanding of the involvement of miRNAs in regulating tumor-associated macrophages (TAMs) and how these TAM-related miRNAs (TRMs) modulate cancer progression is still in its infancy. This study aims to explore the prognostic value of TRMs in breast cancer via the construction of a novel TRM signature. Potential TRMs were identified from the literature, and their prognostic value was evaluated using 1063 cases in The Cancer Genome Atlas Breast Cancer database. The TRM signature was further validated in the external Gene Expression Omnibus GSE22220 dataset. Gene sets enrichment analyses were performed to gain insight into the biological functions of this TRM signature. An eleven-TRM signature consisting of mir-21, mir-24-2, mir-125a, mir-221, mir-22, mir-501, mir-365b, mir-660, mir-146a, let-7b and mir-31 was constructed. This signature significantly differentiated the high-risk group from the low-risk in terms of overall survival (OS)/ distant-relapse free survival (DRFS) (p value < 0.001). The prognostic value of the signature was further enhanced by incorporating other independent prognostic factors in a nomogram-based prediction model, yielding the highest AUC of 0.79 (95% CI: 0.72−0.86) at 5-year OS. Enrichment analyses confirmed that the differentially expressed genes were mainly involved in immune-related pathways such as adaptive immune response, humoral immune response and Th1 and Th2 cell differentiation. This eleven-TRM signature has great potential as a prognostic factor for breast cancer patients besides unravelling the dysregulated immune pathways in high-risk breast cancer.