The No Specific Molecular Profile (NSMP) subtype accounts for ∼30%-40% of endometrial cancer (EC), comprising a heterogeneous group of EC. The primary outcome of this study was the prevalence of actionable genomic alterations in NSMP EC, classified according to the European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of molecular Targets (ESCAT). Oncogenic and likely oncogenic alterations, pathways, and co-mutation patterns were reported. The analysis was stratified by risk group according to the European Society of Gynaecological Oncology (ESGO)-ESMO-European SocieTy for Radiotherapy and Oncology (ESTRO) guidelines. Patients with NSMP EC enrolled in the FPG500 comprehensive cancer genome profiling program (NCT06020625) were included. Two hundred and fifty-three patients with NSMP EC of any International Federation of Gynecology and Obstetrics (FIGO) stage were enrolled between 1 January 2022 and 31 December 2023. Median age was 62 years, and the most frequent histotype was endometrioid (97%). Ninety-five percent of patients were estrogen receptor positive. Two hundred and thirty-three patients (92%) had at least one ESCAT tier I-III alteration. The most frequent variants were in PTEN [88%, 95% confidence interval (CI) 84% to 92%], PIK3CA (42%, 95% CI 36% to 49%), FGFR2 (15%, 95% CI 11% to 20%), and AKT1 (6%, 95% CI 3% to 10%); 4% (95% CI 2% to 8%) of patients had an ESR1 variant, while KRAS G12C was found in 3% (95% CI 1% to 6%) of patients. The majority of PTEN variants were on the R130 hotspot. More frequent PIK3CA hotspot variants were H1047R (9%), E545D/K/Q/A (6%), and E542K (4%). In the overall population, PIK3CA with PIK3R1 (odds ratio [OR] = 0.07, P value = 4.25 × 10^-14), KRAS with CTNNB1 (OR = 0.03, P value = 1.98 × 10^-7), and AKT1 and PTEN (OR = 0.06, P value = 5.73 × 10^-6) were mutually exclusive. Significant co-occurrence was found between PTEN and ARID1A (OR = 6.94, P value = 3.39 × 10^-6) and PTEN with PIK3R1 (OR = 4.36, P value = 0.009). An alteration in the phosphatidylinositol-3 kinase (PI3K) pathway was found in 94% of patients in the overall population and in 98% of patients with an ESCAT tier I-III alteration. Our findings highlight potentially actionable alterations in NSMP EC patients, supporting the exploration of tailored molecular-matched therapies according to risk groups.

Background/Objectives: The accurate prediction of adverse drug reactions (ADRs) to oncological treatments still poses a clinical challenge. Chemotherapy is usually selected based on clinical trials that do not consider patient variability in ADR risk. Consequently, many patients undergo multiple treatments to find the appropriate medication or dosage, enhancing ADR risks and increasing the chance of discontinuing therapy. We first aimed to develop a pharmacogenetic model for predicting chemotherapy-induced ADRs in cancer patients (the ANTIBLASTIC DRUG MULTIPANEL PLATFORM) and then to assess its feasibility and validate this model in patients with non-small-cell lung cancer (NSCLC) undergoing oncological treatments. Methods: Seventy NSCLC patients of all stages that needed oncological treatment at our facility were enrolled, reflecting the typical population served by our institution, based on geographic and demographic characteristics. Treatments followed existing guidelines, and patients were continuously monitored for adverse reactions. We developed and used a multipanel platform based on 326 SNPs that we identified as strongly associated with response to cancer treatments. Subsequently, a network-based algorithm to link these SNPs to molecular and biological functions, as well as efficacy and adverse reactions to oncological treatments, was used. Results: Data and blood samples were collected from 70 NSCLC patients. A bioinformatic analysis of all identified SNPs highlighted five clusters of patients based on variant aggregations and the associated genes, suggesting potential susceptibility to treatment-related toxicity. We assessed the feasibility of the platform and technically validated it by comparing NSCLC patients undergoing the same course of treatment with or without ADRs against the cluster combination. An odds ratio analysis confirmed the correlation between cluster allocation and increased ADR risk, indicating specific treatment susceptibilities. Conclusions: The ANTIBLASTIC DRUG MULTIPANEL PLATFORM was easily applicable and able to predict ADRs in NSCLC patients undergoing oncological treatments. The application of this novel predictive model could significantly reduce adverse drug reactions and improve the rate of chemotherapy completion, enhancing patient outcomes and quality of life. Its potential for broader prescription management suggests significant treatment improvements in cancer patients.

The epidemiological surge of early-onset colorectal cancer (EOCRC) is characterized by accelerated biological kinetics and disproportionately high rates of systemic relapse following curative-intent surgery. Because standard anatomical staging (TNM) lacks the resolution to accurately capture the intrinsic regenerative capacity of microscopic residual disease, we investigated the transcriptomic architecture of post-surgical failure in a strictly defined, curative-intent clinical pan-cohort. Unbiased transcriptomic profiling of the localized (M0) discovery sub-cohort identified IGF2 as the most significantly upregulated correlate of metachronous relapse. High-resolution isoform analysis revealed that this transcriptional output is predominantly driven by the embryonic (P4) and placental (P5) promoters. Systematic allele-specific expression (ASE) analysis supported widespread biallelic IGF2 expression consistent with relaxation of imprinting-domain control. This signal was not restricted to relapsing tumors, suggesting a recurrence-independent oncofetal baseline across the EOCRC spectrum. Because this foundational epigenetic unlocking is functionally insufficient on its own to execute systemic metastasis, we distilled the additional transcriptional plasticity required for dissemination into an internally derived and bootstrap-stabilized 5-gene recurrence-risk module Multivariable analysis across the combined pan-cohort supported an independent association between the high-risk module and systemic relapse (p < 0.001), capturing prognostic dimensions completely unresolved by classical pathological covariates and baseline staging. Ultimately, our findings reframe EOCRC aggressiveness as the product of a dual-hit architecture. This framework resolves the clinical paradox of widespread IGF2 LOI co-existing with heterogeneous outcomes, offering a biologically grounded basis for molecular risk stratification beyond anatomical boundaries.