Onco, Volume 4, Issue 3 (September 2024) – 3 articles

As precision medicine such as targeted therapy and immunotherapy often have limited accessibility, low response rate, and evolved resistance, it is urgent to develop simple, low-cost, and quick-turnaround personalized diagnostic technologies for drug response prediction with high sensitivity, speed, and accuracy. The major challenges of drug response prediction strategies employing digital database modeling are the scarcity of labeled clinical data, applicability only to a few classes of drugs, and losing the resolution at the individual patient level. Although these challenges have been partially addressed by large-scale cancer cell line datasets and more patient-relevant cell-based systems, the integration of different data types and data translation from pre-clinical to clinical utilities are still far-fetched. To overcome the current limitations of precision medicine with a clinically proven drug response prediction assay, we have developed an innovative and proprietary technology based on in vitro patient testing and in silico data analytics. First, a patient-derived gene expression signature was established via the transcriptomic profiling of cell-free mRNA (cfmRNA) from the patient’s blood. Second, a gene-to-drug data fusion and overlaying mechanism to transfer data were performed. Finally, a semi-supervised method was used for the database searching, matching, annotation, and ranking of drug efficacies from a pool of ~700 approved, investigational, or clinical trial drug candidates. A personalized drug response report can be delivered to inform clinical decisions within a week. The PGA (patient-derived gene expression-informed anticancer drug efficacy) test has significantly improved patient outcomes when compared to the treatment plans without PGA support. The implementation of PGA, which combines patient-unique cfmRNA fingerprints with drug mapping power, has the potential to identify treatment options when patients are no longer responding to therapy and when standard-of-care is exhausted. Full article

Background: PD1 and its ligand PD-L1 are related to prognosis in many solid tumors; however, their role in oral squamous cell carcinoma (OSCC) remains unclear. Methods: A retrospective monocentric study including all patients with OSCC diagnosed and treated between January 2020 and May 2022 was performed. PD-L1 expression was assessed per a combined positive score (CPS), considering a CPS of > or equal to 1 as positive (1–20 indicating “low expression” and ≥20 indicating “high”). A descriptive analysis of the patient cohort and tumors was performed, including tumor size, stage, lymph node involvement, recurrence, and survival. Results: In total, 65 patients (65 tumors) were analyzed. A total of 66.15% of the tumors were in advanced stages (III-IV), of which 97.67% expressed PD-L1+, compared with 71.42% in the early stages (I–II). T4 tumors expressed PD-L1 in 100% of cases, compared with 54% in T1 tumors. A total of 50.79% of the tumors showed lymph node involvement (pN+), with 100% of the pN+ showing PD-L1+. The prevalence of pN+ was 59.38% vs. 40.63% for high vs. low PD-L1 expression, respectively. Patients’ follow-ups ranged from 2 to 34.5 months. No significant difference was seen between overall survival (OS) and PD-L1 +/− (CPS ≥ 1 vs. CPS < 1) or high (CPS ≥ 20) and low (CPS < 20) PD-L1 expression (p < 0.97 and 0.64, respectively). Conclusions: The method used to measure PD-L1 (a laboratory test with Dako 22C3 anti-PD-L1 primary antibodies) was reliable and accurate, with a correlation coefficient between PD-L1 expression in the biopsy and the surgical piece of 0.83 (p < 0.0001). A CPS of ≥1 was observed in large tumors (p < 0.001) and was correlated with that of lymph node metastases (p < 0.004). Further analysis of PD-L1 expression in OSCC and studies to determine its relevance in tumor biology and prognosis is needed. Full article

Immunotherapy has paved the way for the development of solid tumor new treatments in the last decade. The approval of immune checkpoint inhibitors such as anti PD-1/PD-L1 provided a revolution with optimal results. However, a considerable proportion of patients experience adverse therapeutic effects, and up to 50% may develop secondary resistance in the first three to five years. This has prompted the need for identifying new targets for immunotherapy that have good tolerance and biosafety and, of course, good tumoral response, either alone or in combination. Two of these new targets are the Lymphocyte-activation gene 3 (LAG-3) and the T cell immunoglobulin and ITIM domain (TIGIT). They are responsible for several interactions with the immune system, prompting an immunosuppressive phenotype in the tumor microenvironment. Both LAG-3 and TIGIT can be druggable, alone or in combination with anti-PD-1/PD-L1, with rather safe profiles making them attractive. In this review, we highlight some of the immune mechanisms of TIGIT and LAG-3 and their detection by immunohistochemistry, providing some insight into their use in the clinical setting. Full article