APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research.

INTRODUCTION: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several studies have been aimed at identifying biomarkers able to predict benefit from these therapies and create a prediction model of response, despite this there is a lack of information to help clinicians in the choice of therapy for lung cancer patients with advanced disease. This is primarily due to the complexity of lung cancer biology, where a single or few biomarkers are not sufficient to provide enough predictive capability to explain biologic differences; other reasons include the paucity of data collected by single studies performed in heterogeneous unmatched cohorts and the methodology of analysis. In fact, classical statistical methods are unable to analyze and integrate the magnitude of information from multiple biological and clinical sources (eg, genomics, transcriptomics, and radiomics). METHODS AND OBJECTIVES: APOLLO11 is an Italian multicentre, observational study involving patients with a diagnosis of advanced lung cancer (NSCLC and SCLC) treated with innovative therapies. Retrospective and prospective collection of multiomic data, such as tissue- (eg, for genomic, transcriptomic analysis) and blood-based biologic material (eg, ctDNA, PBMC), in addition to clinical and radiological data (eg, for radiomic analysis) will be collected. The overall aim of the project is to build a consortium integrating different datasets and a virtual biobank from participating Italian lung cancer centers. To face with the large amount of data provided, AI and ML techniques will be applied will be applied to manage this large dataset in an effort to build an R-Model, integrating retrospective and prospective population-based data. The ultimate goal is to create a tool able to help physicians and patients to make treatment decisions. CONCLUSION: APOLLO11 aims to propose a breakthrough approach in lung cancer research, replacing the old, monocentric viewpoint towards a multicomprehensive, multiomic, multicenter model. Multicenter cancer datasets incorporating common virtual biobank and new methodologic approaches including artificial intelligence, machine learning up to deep learning is the road to the future in oncology launched by this project.

TK-1, TP, Ang-2, and Tie-2 mRNA expression in plasma-derived microvesicles of chemo-refractory metastatic colorectal cancer patients.

BACKGROUND: Trifluridine/tipiracil and regorafenib are indicated for metastatic colorectal cancer (mCRC) patients' refractory to standard chemotherapy. No prognostic or predictive biomarkers are available for these agents. METHODS: We assessed messenger ribonucleic acid (mRNA) expression of four biomarkers implicated in the mechanism of action of trifluridine/tipiracil (TK-1 and TP) and regorafenib (Ang-2 and Tie-2) in baseline plasma-derived microvesicles of chemo-refractory mCRC patients treated with these agents (trifluridine/tipiracil cohort and regorafenib cohort), to explore their prognostic and predictive role. RESULTS: Baseline characteristics of the two cohorts were not different. Ang-2 mRNA was not detectable. Only TK-1 expression measured as a continuous variable was associated with progression-free survival (HR=1.09, 95%CI: 0.99-1.21; p=0.07) and overall survival (HR=1.11, 95%CI: 1.00-1.22; p=0.04), confirmed at multivariate analysis for progression-free survival (p=0.02) with a positive trend for overall survival (p=0.08). Baseline mRNA levels of TK-1, TP and Tie-2 were not predictive of trifluridine/tipiracil and regorafenib benefit. CONCLUSION: Baseline mRNA levels of TK-1, TP and Tie-2 on plasma-derived microvesicles were not predictive of trifluridine/tipiracil and regorafenib benefit. Future studies should analyze the early modulation of these biomarkers to assess their potential predictive role.

Primary Tumor Resection in Synchronous Metastatic Colorectal Cancer Patients Treated with Upfront Chemotherapy plus Bevacizumab: A Pooled Analysis of TRIBE and TRIBE2 Studies.

BACKGROUND: The decision to resect or not the primary tumor in asymptomatic patients with synchronous metastatic colorectal cancer (mCRC) is a complex and challenging issue for oncologists, especially when an antiangiogenic-based therapy is planned. METHODS: Patients enrolled in the phase III TRIBE and TRIBE2 studies that compared upfront FOLFOXIRI + bevacizumab to FOLFIRI or FOLFOX + bevacizumab, respectively, were included. We assessed the association of primary tumor resection (PTR) with progression-free survival (PFS), overall survival (OS), response rate (ORR), rate of grade > 2 adverse events (AEs), and serious gastrointestinal and surgical AEs in the overall population and according to the treatment arm. RESULTS: Of the 999 patients included, 513 (51%) underwent PTR at baseline. Longer PFS and OS were observed in resected patients compared to those with unresected primary tumors: 11.2 vs. 10.0 months (p < 0.001) and 26.6 vs. 22.5 (p < 0.001), respectively. In multivariate models, PTR was confirmed as an independent prognostic factor for better PFS (p = 0.032) and OS (p = 0.018). Patients with PTR experienced a higher incidence of grade 3 or 4 diarrhea (p = 0.055) and lower incidence of anemia (p = 0.053), perforation (p = 0.015), and serious gastrointestinal and surgical AEs (p < 0.001). No statistically significant differences were noted in incidence of bleeding (p = 0.39). The benefit of FOLFOXIRI + bevacizumab in terms of PFS (p for interaction: 0.46), OS (p for interaction: 0.80), ORR (p for interaction: 0.36), and incidence of grade 3 or 4 AEs was independent of PTR. CONCLUSIONS: PTR at baseline was independently associated with good prognosis in synchronous mCRC patients and with lower incidence of serious gastrointestinal and surgical AEs during upfront chemotherapy plus bevacizumab. The benefit and toxicity profile of FOLFOXIRI plus bevacizumab was independent of PTR.

Long-term outcomes and persistent toxicities following BRAF/MEK inhibitor therapy for advanced melanoma.

BACKGROUND: Recent studies have shown that approximately 20% of patients have 4-5 year progression free survival (PFS) on BRAF/MEK inhibitors. The long-term safety and efficacy in these patients with more durable responses have not been studied. METHODS: This retrospective multicenter cohort study assessed response, progression, and adverse events in patients from eight institutions in four countries with >4-year PFS following BRAF/MEK inhibitors. RESULTS: Among 146 patients, 112 (76.7%) remained progression-free at median follow-up of 7.8 years from treatment start; 131 (89.7%) were alive. Among progressors (n = 34), 21 (62%) were on treatment at progression. Among those who discontinued treatment for reasons other than progression (toxicity, preference, etc.) (n = 68, with median 49 months treatment duration), 13 (19%) progressed (median 15.3 months from treatment cessation to progression). Surgery or radiation for single-organ progression resulted in durable benefit in 11 of 22 patients (50%). Subsequent systemic therapy included immune therapy (24% responded) and BRAF/MEK rechallenge (56% responded). Thirteen (8.9%) patients had ongoing toxicities at last follow-up, 10 (77%) of which remained on active treatment; all cardiac adverse events had resolved (n = 9). Twenty-four (16.4%) patients developed any new primary cancer, and 28 (19%) patients experienced other major health events. CONCLUSIONS: Over 75% of patients with 4-year PFS from BRAF/MEK inhibitors had continued durable antitumor responses after nearly 8-year median follow-up, with similar results in patients who discontinued therapy for reasons other than progression. Long-term toxicities were uncommon and low-grade. These findings highlight the often-favourable outcomes in patients with extended benefit from BRAF/MEK inhibitors.

PEOPLE (NTC03447678), a phase II trial to test pembrolizumab as first-line treatment in patients with advanced NSCLC with PD-L1 <50%: a multiomics analysis.

BACKGROUND: Chemoimmunotherapy represents the standard of care for patients with advanced non-small cell lung cancer (NSCLC) and programmed death-ligand 1 (PD-L1) <50%. Although single-agent pembrolizumab has also demonstrated some activity in this setting, no reliable biomarkers yet exist for selecting patients likely to respond to single-agent immunotherapy. The main purpose of the study was to identify potential new biomarkers associated with progression-free-survival (PFS) within a multiomics analysis. METHODS: PEOPLE (NTC03447678) was a prospective phase II trial evaluating first-line pembrolizumab in patients with advanced EGFR and ALK wild type treatment-naïve NSCLC with PD-L1 <50%. Circulating immune profiling was performed by determination of absolute cell counts with multiparametric flow cytometry on freshly isolated whole blood samples at baseline and at first radiological evaluation. Gene expression profiling was performed using nCounter PanCancer IO 360 Panel (NanoString) on baseline tissue. Gut bacterial taxonomic abundance was obtained by shotgun metagenomic sequencing of stool samples at baseline. Omics data were analyzed with sequential univariate Cox proportional hazards regression predicting PFS, with Benjamini-Hochberg multiple comparisons correction. Biological features significant with univariate analysis were analyzed with multivariate least absolute shrinkage and selection operator (LASSO). RESULTS: From May 2018 to October 2020, 65 patients were enrolled. Median follow-up and PFS were 26.4 and 2.9 months, respectively. LASSO integration analysis, with an optimal lambda of 0.28, showed that peripheral blood natural killer cells/CD56dimCD16+ (HR 0.56, 0.41-0.76, p=0.006) abundance at baseline and non-classical CD14dimCD16+monocytes (HR 0.52, 0.36-0.75, p=0.004), eosinophils (CD15+CD16-) (HR 0.62, 0.44-0.89, p=0.03) and lymphocytes (HR 0.32, 0.19-0.56, p=0.001) after first radiologic evaluation correlated with favorable PFS as well as high baseline expression levels of CD244 (HR 0.74, 0.62-0.87, p=0.05) protein tyrosine phosphatase receptor type C (HR 0.55, 0.38-0.81, p=0.098) and killer cell lectin like receptor B1 (HR 0.76, 0.66-0.89, p=0.05). Interferon-responsive factor 9 and cartilage oligomeric matrix protein genes correlated with unfavorable PFS (HR 3.03, 1.52-6.02, p 0.08 and HR 1.22, 1.08-1.37, p=0.06, corrected). No microbiome features were selected. CONCLUSIONS: This multiomics approach was able to identify immune cell subsets and expression levels of genes associated to PFS in patients with PD-L1 <50% NSCLC treated with first-line pembrolizumab. These preliminary data will be confirmed in the larger multicentric international I3LUNG trial (NCT05537922). TRIAL REGISTRATION NUMBER: 2017-002841-31.

Systemic lupus erythematosus reactivation after chemoimmunotherapy in preexisting autoimmune disease.

The use of immune checkpoint inhibitors (ICIs) offers new possibilities in modern treatment of many types of cancers. Few data regarding safety and efficacy of ICIs are available, and are mainly from retrospective studies and case reports rather than from clinical trials, in the context of preexisting autoimmune disease, mainly due to the risk of severe toxicity. We present an unexpected life-threatening reactivation of systemic lupus erythematosus after one dose of chemo-immunotherapy with pembrolizumab for oligometastatic non-small-cell lung cancer. We analyze data coming from the published literature in this setting and discuss the risk-benefit balance of immunotherapy in patients with preexisting severe autoimmune disease.

Prognostic and Predictive Role of Body Mass Index (BMI) in Metastatic Colorectal Cancer (mCRC): A Pooled Analisys of Tribe and Tribe-2 Studies by GONO.

BACKGROUND: Obesity is associated with an increased risk of development and recurrence of colorectal cancer. The role of obesity in metastatic colorectal cancer patients (pts) is still unclear, especially in those treated with triplet plus bevacizumab (bev). The aim of our study was to evaluate the prognostic and predictive role of BMI in metastatic colorectal cancer pts treated with FOLFOXIRI plus bev or FOLFIRI/FOLFOX plus bev in the TRIBE and TRIBE-2 trial. MATERIALS AND METHODS: A total of 1160 pts enrolled in TRIBE and TRIBE-2 trials were included. Baseline height and weight were used to assign pts to one of the following BMI categories: underweight (group A = BMI <18.5 kg/m2; 52 pts), normal (group B = BMI 18.5-29.9 kg/m2; 952 pts) and obese (group C > 30 kg/m2; 156 pts). RESULTS: In our population, no differences in terms of PFS (P = .43) or OS (P = .99) resulted between 3 groups. No interaction effect between treatment arm and BMI was evident in terms of PFS (Group A HR: 0.65 [95%CI: 0.36-1.16]; Group B HR: 0.77 [95%CI: 0.67-0.88]; Group C HR: 0.67 [95%CI: 0.48-0.93]; P for interaction = .75) or OS (Group A HR: 0.57 [95%CI: 0.29-1.12]; Group B HR: 0.85 [95%CI: 0.73-0.99];Group C HR: 0.69 [95%CI: 0.48-1.01] P for interaction = .36). No statistically significant difference in terms of dose reductions due to toxicities were found according to BMI in the overall population (P = .48) and in pts treated with FOLFOXIRI plus bev (P = .57). CONCLUSION: BMI was neither prognostic or predictive for PFS and OS in our population. Our analyses showed that the advantage of FOLFOXIRI plus bev versus FOLFIRI/FOLFOX plus bev was independent from BMI.

Efficacy of mRNA anti-SARS-CoV-2 vaccination and dynamics of humoral immune response in patients with solid tumors: results from the institutional registry of an Italian tertiary cancer center.

Background: Systemic immunosuppression characterizing cancer patients represents a concern regarding the efficacy of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination, and real-world evidence is needed to define the efficacy and the dynamics of humoral immune response to mRNA-based anti-SARS-CoV-2 vaccines. Methods: We conducted an observational study that included patients with solid tumors who were candidates for mRNA anti-SARS-CoV-2 vaccination at the Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy. The primary objective was to monitor the immunologic response to the mRNA anti-SARS-CoV-2 vaccination in terms of anti-spike antibody levels. All the patients received two doses of the mRNA-1273 vaccine or the BNT162b2 vaccine. Healthcare workers served as a control group of healthy subjects. Results: Among the 243 patients included in the present analysis, 208 (85.60%) and 238 (97.94%) resulted seroconverted after the first and the second dose of vaccine, respectively. Only five patients (2.06%) had a negative titer after the second dose. No significant differences in the rate of seroconversion after two vaccine doses were observed in patients as compared with the control group of healthy subjects. Age and anticancer treatment class had an independent impact on the antibody titer after the second dose of vaccination. In a subgroup of 171 patients with available data about the third timepoint, patients receiving immunotherapy with immune checkpoint inhibitors seem to have a higher peak of antibodies soon after the second dose (3 weeks after), but a more pronounced decrease at a late timepoint (3 months after). Conclusions: The systemic immunosuppression characterizing cancer patients did not seem to dramatically affect the humoral response to anti-SARS-CoV-2 mRNA vaccines in our population of patients with solid tumors. Further investigation is needed to dissect the interplay between immunotherapy and longitudinal dynamics of humoral response to mRNA vaccines, as well as to analyze the cellular response to mRNA vaccines in cancer patients.

Real-world data to build explainable trustworthy artificial intelligence models for prediction of immunotherapy efficacy in NSCLC patients.

Introduction: Artificial Intelligence (AI) methods are being increasingly investigated as a means to generate predictive models applicable in the clinical practice. In this study, we developed a model to predict the efficacy of immunotherapy (IO) in patients with advanced non-small cell lung cancer (NSCLC) using eXplainable AI (XAI) Machine Learning (ML) methods. Methods: We prospectively collected real-world data from patients with an advanced NSCLC condition receiving immune-checkpoint inhibitors (ICIs) either as a single agent or in combination with chemotherapy. With regards to six different outcomes - Disease Control Rate (DCR), Objective Response Rate (ORR), 6 and 24-month Overall Survival (OS6 and OS24), 3-months Progression-Free Survival (PFS3) and Time to Treatment Failure (TTF3) - we evaluated five different classification ML models: CatBoost (CB), Logistic Regression (LR), Neural Network (NN), Random Forest (RF) and Support Vector Machine (SVM). We used the Shapley Additive Explanation (SHAP) values to explain model predictions. Results: Of 480 patients included in the study 407 received immunotherapy and 73 chemo- and immunotherapy. From all the ML models, CB performed the best for OS6 and TTF3, (accuracy 0.83 and 0.81, respectively). CB and LR reached accuracy of 0.75 and 0.73 for the outcome DCR. SHAP for CB demonstrated that the feature that strongly influences models' prediction for all three outcomes was Neutrophil to Lymphocyte Ratio (NLR). Performance Status (ECOG-PS) was an important feature for the outcomes OS6 and TTF3, while PD-L1, Line of IO and chemo-immunotherapy appeared to be more important in predicting DCR. Conclusions: In this study we developed a ML algorithm based on real-world data, explained by SHAP techniques, and able to accurately predict the efficacy of immunotherapy in sets of NSCLC patients.

Carcinomatosis under control by osimertinib in EGFR and TP53 mutated lung adenocarcinoma.

INTRODUCTION: Approximately 25%-30% of patients with non-small cell lung cancer (NSCLC) develop central nervous system (CNS) metastases during the course of the disease; this percentage is higher in patients with epidermal growth factor receptor (EGFR) mutations. Leptomeningeal metastases, infrequent in the advanced setting, have a particularly dismal prognosis. Osimertinib, a third-generation EGFR inhibitor, can provide effective and durable response in this setting. CASE DESCRIPTION: We present a 62-year-old man with progressive vomiting, headache, short-term memory impairment, and left lower limb hyposthenia. Computed tomography (CT) showed bilateral lung nodules, multiple lymphadenopathies, liver and bone metastases, and CNS and leptomeningeal dissemination, including multiple parenchymal nodules located at supra- and infratentorial brain. Bone needle biopsy documented TTF1+ lung adenocarcinoma. Whole brain radiotherapy (WBRT) and symptomatic treatments were started. Next-generation sequencing reported deletion of exon 19 of EGFR and mutation 8 of TP53. Osimertinib 80 mg was promptly started and WBRT interrupted. Some days after the patient experienced repetitive seizures and neurologic worsening, antiepileptic drugs and dexamethasone were implemented, with gradual improvement. Radiologic evaluation, including brain MRI and thorax-abdominal CT, showed partial response on CNS as well as extracranial sites, which was sustained. CONCLUSIONS: First-line treatment with osimertinib can be safe and effective in EGFR-mutated NSCLC even in presence of multiple negative predictive factors (poor Performance Status, diffuse leptomeningeal involvement, TP53 comutation), suggesting that deferring local treatments can be feasible in this setting, allowing the patient to maintain a good quality of life.