The confluence of new technologies with artificial intelligence (AI) and machine learning (ML) analytical techniques is rapidly advancing the field of precision oncology, promising to improve diagnostic approaches and therapeutic strategies for patients with cancer. By analyzing multi-dimensional, multiomic, spatial pathology, and radiomic data, these technologies enable a deeper understanding of the intricate molecular pathways, aiding in the identification of critical nodes within the tumor’s biology to optimize treatment selection. The applications of AI/ML in precision oncology are extensive and include the generation of synthetic data, e.g., digital twins, in order to provide the necessary information to design or expedite the conduct of clinical trials. Currently, many operational and technical challenges exist related to data technology, engineering, and storage; algorithm development and structures; quality and quantity of the data and the analytical pipeline; data sharing and generalizability; and the incorporation of these technologies into the current clinical workflow and reimbursement models.

PURPOSE: Although checkpoint inhibitors have improved first-line treatment for non–small cell lung cancer (NSCLC), a therapeutic need remains for patients whose disease does not respond or who experience disease progression after anti–PD-L1/PD-1 immunotherapy. CONTACT-01 (ClinicalTrials.gov identifier: NCT04471428 ) evaluated atezolizumab plus cabozantinib versus docetaxel in patients with metastatic NSCLC who developed disease progression after concurrent or sequential treatment with anti–PD-L1/PD-1 and platinum-containing chemotherapy. METHODS: This multicenter, open-label, phase III trial randomly assigned patients 1:1 to atezolizumab 1,200 mg intravenously once every 3 weeks (q3w) plus cabozantinib 40 mg orally once daily or docetaxel 75 mg/m² intravenously once every 3 weeks. The primary end point was overall survival (OS). RESULTS: One hundred eighty-six patients were assigned atezolizumab plus cabozantinib, and 180 docetaxel. Minimum OS follow-up was 10.9 months. Median OS was 10.7 months (95% CI, 8.8 to 12.3) with atezolizumab plus cabozantinib and 10.5 months (95% CI, 8.6 to 13.0) with docetaxel (stratified hazard ratio [HR], 0.88 [95% CI, 0.68 to 1.16]; P = .3668). Median progression-free survival was 4.6 months (95% CI, 4.1 to 5.6) and 4.0 months (95% CI, 3.1 to 4.4), respectively (stratified HR, 0.74 [95% CI, 0.59 to 0.92]). Serious adverse events (AEs) occurred in 71 (38.4%) patients receiving atezolizumab plus cabozantinib and 58 (34.7%) receiving docetaxel. Grade 3/4 treatment-related AEs occurred in 73 (39.5%) patients receiving atezolizumab plus cabozantinib and 58 (34.7%) receiving docetaxel. Grade 5 AEs occurred in 14 (7.6%) and 10 (6.0%) patients in the atezolizumab plus cabozantinib and docetaxel arms, respectively (treatment-related in four [2.2%] and one [0.6%], respectively). CONCLUSION: Atezolizumab plus cabozantinib after disease progression following anti–PD-L1/PD-1 immunotherapy and platinum-containing chemotherapy for metastatic NSCLC did not improve OS compared with docetaxel. Safety was consistent with known profiles of these agents.

Local recurrence is the major manifestation of treatment failure in patients with operable laryngeal carcinoma. Established clinicopathological factors cannot sufficiently predict patients that are likely to recur after treatment. Additional tools are therefore required to accurately identify patients at high risk for recurrence. This study attempts to identify and independently validate gene expression models, prognostic of disease-free survival (DFS) in operable laryngeal cancer. Using Affymetrix U133A Genechips, we profiled fresh-frozen tumor tissues from 66 patients with laryngeal cancer treated locally with surgery. We applied Cox regression proportional hazards modeling to identify multigene predictors of recurrence. Gene models were then validated in two independent cohorts of 54 and 187 patients (fresh-frozen and formalin-fixed tissue validation sets, respectively). We focused on genes univariately associated with DFS (p<0.01) in the training set. Among several models comprising different numbers of genes, a 30-probe set model demonstrated optimal performance in both the training (log-rank, p<0.001) and 1^st validation (p = 0.010) sets. Specifically, in the 1^st validation set, median DFS as predicted by the 30-probe set model, was 34 and 80 months for high- and low-risk patients, respectively. Hazard ratio (HR) for recurrence in the high-risk group was 3.87 (95% CI 1.28–11.73, Wald's p = 0.017). Testing the expression of selected genes from the above model in the 2^nd validation set, with qPCR, revealed significant associations of single markers, such as ACE2, FLOT1 and PRKD1, with patient DFS. High PRKD1 remained an unfavorable prognostic marker upon multivariate analysis (HR = 2.00, 95% CI 1.28–3.14, p = 0.002) along with positive nodal status. We have established and validated gene models that can successfully stratify patients with laryngeal cancer, based on their risk for recurrence. It seems worthy to prospectively validate PRKD1 expression as a laryngeal cancer prognostic marker, for routine clinical applications.

Background The clinical relevance of mismatch repair (MMR) status in patients with nonmetastatic cancer across tumour types remains unclear. Our goal was to investigate the prognostic role of MMR deficiency in patients with stage I-III colorectal and endometrial cancer. Methods Patients with nonmetastatic colorectal and endometrial cancer with tumour tissue available for analysis were identified through the Hellenic Cooperative Oncology Group (HeCOG)’s tumour repository. Patients had been referred to Departments of Medical Oncology affiliated with HeCOG. MMR protein expression was evaluated by immunohistochemistry. The primary outcome measure was overall survival (OS). Results From May 1990 to September 2012, 1158 patients with nonmetastatic colorectal (N = 991) and endometrial cancer (N = 167) were identified (median age: 64 years, men: 544). All patients with colorectal and 109 (65%) with endometrial cancer had received adjuvant treatment. MMR deficiency was observed in 114 (11.5%) of colorectal and 80 (47.9%) of endometrial tumours. More commonly deficient proteins were PMS2 (69 patients, 7%) and MLH1 (63 patients, 6.5%) in colorectal cancer and MSH2 (58 patients, 34.7%) in endometrial cancer. Colorectal MMR-deficient (dMMR) tumours were more likely to be right sided (65 % dMMR vs 27 % proficient MMR, pMMR; p < 0.001), high grade (31% vs 15%, χ², p < 0.001) and with a mucinous component (64% vs 42%, p < 0.001). Endometrial dMMR tumours were more often of endometrioid histology (51.4 % endometrioid vs 20 % serous/clear cell, p = 0.020). Compared with MMR proficiency, MMR deficiency was associated with improved OS in patients with endometrial cancer (HR = 0.38, 95% CI 0.20 to 0.76, p = 0.006), but not in patients with colorectal cancer (HR = 0.73, 95% CI 0.49 to 1.09, p = 0.130). After adjusting for age, stage and grade, MMR deficiency maintained its favourable prognostic significance in patients with endometrial cancer (HR = 0.42, 95% CI 0.20 to 0.88, p = 0.021). Conclusions DMMR was associated with improved outcomes in patients with nonmetastatic endometrial cancer, but not in patients with nonmetastatic colorectal cancer who received adjuvant chemotherapy.

Background We evaluated real-world clinical outcomes and toxicity data and assessed treatment-related costs in patients with advanced breast cancer who received treatment with cyclin-dependent kinase inhibitors (CDKi). Patients and methods We conducted a prospective–retrospective analysis of patients with advanced hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer who received a CDKi, in combination with endocrine therapy, at any line of treatment. The primary endpoint was progression-free survival (PFS). Cost analysis was conducted from a public third-payer (National Organization for Healthcare Services Provision (EOPYY)) perspective, assessing only costs related to direct medical care, including drug therapy costs and adverse drug reaction (ADR)-related costs. Results From July 2015 to October 2019, 365 women received endocrine therapy combined with CDKi; median age was 61 years, postmenopausal 290 (80.6%) patients. CDKi were administered as first-line treatment in 149 (40.9%) patients, second-line treatment in 96 (26.4%) and third-line treatment and beyond in 119 (32.7%) patients. The most common adverse events were neutropenia, anaemia, thrombocytopenia and fatigue. Grade 3–4 adverse events occurred in 86 (23.6%) patients, whereas 8 (2.2%) patients permanently discontinued treatment due to toxicity. The median PFS for patients who received CDKi as first-line, second-line and third-line treatment and beyond was 18.7, 12 and 7.4 months, respectively. The median overall survival since the initiation of CDKi treatment was 29.9 months (95% CI: 23.0–not yet reached (NR)). The mean pharmaceutical therapy cost estimated per cycle was 2 724.12 € for each patient, whereas the main driver of the ADR-related costs was haematological adverse events. Conclusions Treatment with CDKi was well tolerated, with a low drug discontinuation rate. Patients who received CDKi as first-line treatment had improved PFS and OS compared with second-line treatment and beyond. The main component of direct medical costs assessed in the cost analysis comprises CDKi pharmaceutical therapy costs. Trial registration number NCT04133207

The development of checkpoint blockade immunotherapy has transformed the medical oncology armamentarium. But despite its favorable impact on clinical outcomes, immunotherapy benefits only a subset of patients, and a substantial proportion of these individuals eventually manifest resistance. Serious immune-related adverse events and hyperprogression have also been reported. It is therefore essential to understand the molecular mechanisms and identify the drivers of therapeutic response and resistance. In this review, we provide an overview of the current and emerging clinically relevant genomic biomarkers implicated in checkpoint blockade outcome. US Food and Drug Administration–approved molecular biomarkers of immunotherapy response include mismatch repair deficiency and/or microsatelliteinstability and tumor mutational burden of at least 10 mutations/megabase. Investigational genomic-associated biomarkers for immunotherapy response include alterations of the following genes/associated pathways: chromatin remodeling (ARID1A, PBRM1, SMARCA4, SMARCB1, BAP1), major histocompatibility complex, specific (eg, ultraviolet, APOBEC) mutational signatures, T-cell receptor repertoire, PDL1, POLE/POLD1, and neo-antigens produced by the mutanome, those potentially associated with resistance include β2-microglobulin, EGFR, Keap1, JAK1/JAK2/interferon-gamma signaling, MDM2, PTEN, STK11, and Wnt/Beta-catenin pathway alterations. Prospective clinical trials are needed to assess the role of a composite of these biomarkers to optimize the implementation of precision immunotherapy in patient care.