Incongruity between T cell receptor recognition of breast cancer hotspot mutations ESR1 Y537S and D538G following exogenous peptide loading versus endogenous antigen processing.

T cell receptor engineered T cell (TCR T) therapies have shown recent efficacy against certain types of solid metastatic cancers. However, to extend TCR T therapies to treat more patients across additional cancer types, new TCRs recognizing cancer-specific antigen targets are needed. Driver mutations in AKT1, ESR1, PIK3CA, and TP53 are common in patients with metastatic breast cancer (MBC) and if immunogenic could serve as ideal tumor-specific targets for TCR T therapy to treat this disease. Through IFN-γ ELISpot screening of in vitro expanded neopeptide-stimulated T cell lines from healthy donors and MBC patients, we identified reactivity towards 11 of 13 of the mutations. To identify neopeptide-specific TCRs, we then performed single-cell RNA sequencing of one of the T cell lines following neopeptide stimulation. Here, we identified an ESR1 Y537S specific T cell clone, clonotype 16, and an ESR1 Y537S/D538G dual-specific T cell clone, clonotype 21, which were HLA-B*40:02 and HLA-C*01:02 restricted, respectively. TCR Ts expressing these TCRs recognized and killed target cells pulsed with ESR1 neopeptides with minimal activity against ESR1 WT peptide. However, these TCRs failed to recognize target cells expressing endogenous mutant ESR1. To investigate the basis of this lack of recognition we performed immunopeptidomics analysis of a mutant-overexpressing lymphoblastoid cell line and found that the ESR1 Y537S neopeptide was not endogenously processed, despite binding to HLA-B*40:02 when exogenously pulsed onto the target cell. These results indicate that stimulation of T cells that likely derive from the naïve repertoire with pulsed minimal peptides may lead to the expansion of clones that recognize non-processed peptides, and highlights the importance of using methods that selectively expand T cells with specificity for antigens that are efficiently processed and presented.

Prevalence of Cardiomyopathy in Patients with Type 1 Diabetes Mellitus.

Background: Diabetic cardiac muscle disease or diabetic cardiomyopathy (DbCM) comprises a set of myocardial lesions that are not associated with coronary atherosclerosis or high blood pressure. It is characterized by fibrosis and hypertrophy, which ultimately results in heart failure. Diastolic dysfunction (DD) has been shown to be the first manifestation of diabetic cardiomyopathy. Currently, there are few studies on the prevalence of diabetic cardiomyopathy in adult patients diagnosed with type 1 diabetes mellitus (T1D). Methods: The study included 75 adult participants who underwent an echocardiogram. Data on their comorbidities were collected from their medical records and biochemical parameters were analyzed in blood and urine samples. Results: We found that the prevalence of DbCM in our T1D population was more than one-third (34%), which exceeded the prevalence reported in studies with adolescents and that reported in the population without diabetes. Also, we found that the probability of developing DD after 20 years of T1D diagnosis was 78%. Conclusions: Recommendations need to be issued in relation to diabetic cardiomyopathy to carry out secondary prevention in adult patients with T1D. More multicenter studies, which include a larger population, from different regions of the world need to be performed.

DICER1-associated central nervous system sarcoma: A comprehensive clinical and genomic characterization of case series of young adult patients.

Background: DICER1 alterations are associated with intracranial tumors in the pediatric population, including pineoblastoma, pituitary blastoma, and the recently described "primary DICER1-associated CNS sarcoma" (DCS). DCS is an extremely aggressive tumor with a distinct methylation signature and a high frequency of co-occurring mutations. However, little is known about its treatment approach and the genomic changes occurring after exposure to chemoradiotherapy. Methods: We collected clinical, histological, and molecular data from eight young adults with DCS. Genomic analysis was performed by Next-generation Sequencing (NGS). Subsequently, an additional germline variants analysis was completed. In addition, an NGS analysis on post-progression tumor tissue or liquid biopsy was performed when available. Multiple clinicopathological characteristics, treatment variables, and survival outcomes were assessed. Results: Median age was 20 years. Most lesions were supratentorial. Histology was classified as fusiform cell sarcomas (50%), undifferentiated (unclassified) sarcoma (37.5%), and chondrosarcoma (12.5%). Germline pathogenic DICER1 variants were present in two patients, 75% of cases had more than one somatic alteration in DICER1, and the most frequent commutation was TP53. Seven patients were treated with surgery, Ifosfamide, Cisplatin, and Etoposide (ICE) chemotherapy and radiotherapy. The objective response was 75%, and the median time to progression (TTP) was 14.5 months. At progression, the most common mutations were in KRAS and NF1. Overall survival was 30.8 months. Conclusions: DCS is an aggressive tumor with limited therapeutic options that requires a comprehensive diagnostic approach, including molecular characterization. Most cases had mutations in TP53, NF1, and PTEN, and most alterations at progression were related to MAPK, RAS and PI3K signaling pathways.

Integration of artificial intelligence and precision oncology in Latin America.

Next-generation medicine encompasses different concepts related to healthcare models and technological developments. In Latin America and the Caribbean, healthcare systems are quite different between countries, and cancer control is known to be insufficient and inefficient considering socioeconomically discrepancies. Despite advancements in knowledge about the biology of different oncological diseases, the disease remains a challenge in terms of diagnosis, treatment, and prognosis for clinicians and researchers. With the development of molecular biology, better diagnosis methods, and therapeutic tools in the last years, artificial intelligence (AI) has become important, because it could improve different clinical scenarios: predicting clinically relevant parameters, cancer diagnosis, cancer research, and accelerating the growth of personalized medicine. The incorporation of AI represents an important challenge in terms of diagnosis, treatment, and prognosis for clinicians and researchers in cancer care. Therefore, some studies about AI in Latin America and the Caribbean are being conducted with the aim to improve the performance of AI in those countries. This review introduces AI in cancer care in Latin America and the Caribbean, and the advantages and promising results that it has shown in this socio-demographic context.

Bispecific Antibodies in Cancer Immunotherapy: A Novel Response to an Old Question.

Immunotherapy has redefined the treatment of cancer patients and it is constantly generating new advances and approaches. Among the multiple options of immunotherapy, bispecific antibodies (bsAbs) represent a novel thoughtful approach. These drugs integrate the action of the immune system in a strategy to redirect the activation of innate and adaptive immunity toward specific antigens and specific tumor locations. Here we discussed some basic aspects of the design and function of bsAbs, their main challenges and the state-of-the-art of these molecules in the treatment of hematological and solid malignancies and future perspectives.