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Since a non-negligible fraction of patients with metastatic melanoma does not experience long-term disease control, even with immunotherapy and targeted therapy, new biomarkers for patient stratification and treatment tailoring are needed in this setting. We investigated the association of a novel immune-inflammatory blood-based biomarker, the Pan-Immune-Inflammation Value (PIV), with clinical outcomes of patients with metastatic melanoma receiving first-line therapy. We retrospectively included patients treated at the Fondazione IRCCS Istituto Nazionale dei Tumori of Milan and having an available baseline complete blood cell count (CBC). PIV was calculated as: [neutrophil count (103/mm3) × platelet count (103/mm3) × monocyte count (103/mm3)]/lymphocyte count (103/mm3). A total of 228 patients were included: 119 (52%) had been treated with immunotherapy and 109 (48%) with targeted therapy. PIV was significantly higher in patients with ECOG PS ≥ 1, high disease burden, synchronous metastases, and elevated baseline LDH level. High baseline PIV was independently associated with poor overall survival (adjusted hazard ratio [HR]: 2.06; 95% confidence interval [CI]: 1.30–3.29; adjusted P = 0.002) and progression-free survival (adjusted HR 1.56; 95% CI 1.01–2.41; adjusted P = 0.044). High PIV was also associated with primary resistance to both immunotherapy (odds ratio [OR]: 3.98; 95% CI 1.45–12.32; P = 0.005) and targeted therapy (OR: 8.42; 95% CI 2.50–34.5; P < 0.001). PIV showed a promising discrimination ability in terms of AIC and c-index when compared with other CBC-based biomarkers. PIV may guide the treatment decision process and the development of novel first-line treatment strategies in melanoma, but warrants further study and validation.

Neuroendocrine neoplasms of the lung represent about 20% to 30% of all neuroendocrine tumors. On the basis of clinical and pathologic characteristics, 2 different categories of tumors may be defined: poorly differentiated neuroendocrine neoplasms, characterized by a high rate of recurrences and poor prognosis, and well-differentiated neuroendocrine neoplasms (typical carcinoids and atypical carcinoids), which generally display an indolent course. Lung carcinoids represent only 1% to 5% of all lung malignancies, but their incidence has significantly increased over the past 30 years. Surgery is the reference standard of treatment for lung carcinoids with locoregional disease. For advanced or unresectable lung carcinoids, several therapeutic options are available, but the choice should be shared within a multidisciplinary team to ensure optimal therapeutic outcomes. We describe the current management of these rare neoplasms.

Pheochromocytomas and paragangliomas (PPGLs) can metastasize in approximately 15–20% of cases. This review discusses the available evidence on the biology and treatment of metastatic PPGLs. Chemotherapy is the first-line treatment option for this evolving and symptomatic disease. In patients with high MIBG uptake and positive PETGa-68, radiometabolic treatment may be considered. The efficacy of sunitinib has been shown in observational studies, and pembrolizumab has been evaluated in phase II clinical studies, while other agents investigated in this setting are anti-angiogenic drugs cabozantinib, dovitinib, axitinib and lenvatinib. As these agents' efficacy and safety data, alone or in combination, are scant and based on few treated patients, enrollment in clinical trials is mandatory. Future therapeutic options may be represented by DNA repair system inhibitors (such as olaparib), HIF2 inhibitors and immunotherapy.

Background: Hyperprogressive disease (HPD) has been described in ≃14-25% of pretreated non-small cell lung cancer (NSCLC) patients upon single-agent (SA) PD-1/PD-L1 inhibitors (ICI) and has not been reported upon platinum-based chemotherapy (PCT) and ICI combinations. So far, no predictive biomarkers are available for HPD early detection. Methods: NSCLC patients treated with 1st line SA-ICI or PCT-ICI were assessed for HPD and circulating neutrophils. HPD was defined as delta tumor growth rate (TGR) >50% and/or TGR ratio ≥2. Circulating low density neutrophils (LDNs) were assessed by flow cytometry on peripheral blood mononuclear cells (PMBCs). LDNs were defined as CD66b+CD15+ cells among CD11b+ PBMCs and immature subtypes as CD10− LDNs. The LDNs predictive role was assessed by penalized model-based tests. Results: 144 NSCLC patients were included: 75 treated with SA-ICI, 69 with PCT-ICI. In the SA-ICI cohort, HPD occurred in 8 (11%) patients, while progressive disease (PD) and response or stable disease (PR/SD) occurred in 33 (44%) and 34 (45%) of patients respectively. Immature circulating CD10− LDNs were significantly higher in baseline blood samples of HPD patients [median (ME): 39.3, interquartile range (IQR): 28.7] compared to PD [ME: 7.4, IQR: 14.9, p Conclusions: Baseline circulating immature neutrophils characterize HPD upon 1st line SA-ICI and a 30.5% cut-off of immature neutrophils could select NSCLC patients to be addressed to PCT-ICI combinations. Citation Format: Roberto Ferrara, Giuseppe Lo Russo, Chiara Maura Ciniselli, Annamaria Piva, Barbara Bassani, Elena Jachetti, Giuseppina Calareso, Valeria Duroni, Settimio Di Gregorio, Claudia Proto, Arsela Prelaj, Alessandro De Toma, Mario Occhipinti, Marta Brambilla, Sara Manglaviti, Laura Mazzeo, Arturo Rinaldi, Teresa Beninato, Monica Ganzinelli, Filippo De Braud, Marina Chiara Garassino, Paolo Verderio, Mario Paolo Colombo, Sabina Sangaletti. Circulating immature neutrophils early detect hyperprogressive disease upon first-line PD-1/PD-L1 inhibitors in non-small cell lung cancer patients selecting best candidates for platinum-based chemotherapy and PD-1/PD-L1 inhibitors combinations. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5506.

Simple Summary In this paper, the authors show that artificial intelligence (AI) and machine learning (ML) are useful approaches to integrate multifactorial data and helpful for personalized prediction. In detail, compared to PD-L1 for advanced non-small cell lung cancer (NSCLC), ML tools predicted better responder (R) and non-responder (NR) patients to immunotherapy (IO). It was also able to indirectly foresee OS and PFS of R and NR patients. Given the high incidence of NSCLC, and the absence of reliable biomarkers to predict the response to IO other than PD-L1, the authors believe this research may be of great interest to anyone involved in thoracic oncology. Furthermore, given the growing interest from the scientific community in AI and ML, the authors believe that this manuscript could represent a fascinating topic to anyone who needs to exploit the enormous potential of these tools in the treatment of cancer. Abstract (1) Background: In advanced non-small cell lung cancer (aNSCLC), programmed death ligand 1 (PD-L1) remains the only biomarker for candidate patients to immunotherapy (IO). This study aimed at using artificial intelligence (AI) and machine learning (ML) tools to improve response and efficacy predictions in aNSCLC patients treated with IO. (2) Methods: Real world data and the blood microRNA signature classifier (MSC) were used. Patients were divided into responders (R) and non-responders (NR) to determine if the overall survival of the patients was likely to be shorter or longer than 24 months from baseline IO. (3) Results: One-hundred sixty-four out of 200 patients (i.e., only those ones with PD-L1 data available) were considered in the model, 73 (44.5%) were R and 91 (55.5%) NR. Overall, the best model was the linear regression (RL) and included 5 features. The model predicting R/NR of patients achieved accuracy ACC = 0.756, F1 score F1 = 0.722, and area under the ROC curve AUC = 0.82. LR was also the best-performing model in predicting patients with long survival (24 months OS), achieving ACC = 0.839, F1 = 0.908, and AUC = 0.87. (4) Conclusions: The results suggest that the integration of multifactorial data provided by ML techniques is a useful tool to select NSCLC patients as candidates for IO.

Patients affected by inoperable lung cancer, due to great extension or to the presence of metastases, are currently treated with intravenous drugs that act on immune system activation alone or in combination with chemotherapy as first-line treatment. The characteristics of these patients (both their medical history and their blood exams) need to be studied to find out if some of them can help clinicians to predict if they will benefit from the combination of immunotherapy with chemotherapy. The authors collected the data of patients with advanced lung cancer treated in their hospital and found out that a value calculated from their blood exams, collected before the start of treatment and a combination of values named EPSILoN score (which considers patients' clinical condition, their history of tobacco smoking, the presence of metastases in the liver and two blood exam parameters, namely the neutrophil-to-lymphocyte ratio and LDH level) can predict how their disease will evolve during first-line treatment with chemotherapy in combination with immunotherapy.

9057 Background: Immune checkpoint inhibitors (IO) single agent or in combination with platinum chemotherapy (CT-IO) are standard of care for Stage IV non-small cell lung cancer (NSCLC) according to PD-L1 expression. While the efficacy of IO among patients (pts) with common EGFR and ALK alterations appears to be limited, its activity in pts with novel oncogenic drivers alterations is not well characterized. Compared to non-oncogene-addicted NSCLC, the overall response rate (ORR) seems to be similar in BRAF and c-MET altered NSCLC, lower in RET altered NSCLC, while data are less consistent in HER2 and EGFR exon 20 (EGFRex20) altered NSCLCs. Methods: From January 2016 to January 2022, we retrospectively enrolled pts with Stage IV NSCLC that received IO or combination CT– IO in any line, ECOG PS 0 - 2 and detection of MET exon 14 skipping mutations (METex14), BRAF mutations (V600E or non-V600E), RET rearrangement, HER2 point mutations (HER2mut)/exon 20 insertions (HER2ex20) or uncommon EGFR mutations (uEGFRmut)/EGFRex20. A review of clinicopathologic and molecular features and an analysis of response to combination or single-agent IO were conducted. Results: Among sixty-four pts enrolled, 20 (31%) had METex14, 19 (30%) had EGFR alterations [12 (19%) EGFRex20, 7 (11%) uEGFRmut], 8 (12%) had BRAF mutation (3 V600E and 5 non-V600E), 13(20%) had HER2 alterations [7 (11%) HER2ex20, 6 (10%) HER2mut] and 4 (6%) were RET rearranged. 43 received IO single agent and 21 received CT-IO. With a median follow up of 22 months (m), median progression free survival (mPFS) was 5.40 m (0.95 CI 4.73-6.9) overall, 6.77m in CT-IO arm (0.95 CI 5.37-NA) and 5.10m in IO arm (0.95 CI 2.60-6.7), with a trend to better mPFS for CT-IO (p 0.054). Regarding specific mutations irrespectively from treatment arm, NSCLC harboring METex14 showed a mPFS of 5.33 m (0.95 CI, 2.30-13.9), BRAF 9.9 m (0.95 CI, 6.70-NA), EGFR 4.93 m (0.95 CI, 1.80-6.9), HER2 11.4 (0.95 CI, 4.2-NA), RET 5.28 (0.95 CI, 1.42-NA). Disease control rate (DCR) was better in the CT-IO arm vs IO one in the overall population (84.2% vs 50%, p 0.013). Conclusions: Novel driver alterations seem to show a benefit from IO treatments. CT-IO seems to have a better outcome in terms of DCR. Therefore, IO-based treatment should be evaluated also in tumors harboring novel driver alterations. [Table: see text]

Immune-checkpoint inhibitors (ICIs) have significantly improved outcome of advanced non-small cell lung cancer (aNSCLC) patients. However, their efficacy remains uncertain in uncommon histologies (UH).Data from ICI treated aNSCLC patients (April,2013-January,2021) in one Institution were retrospectively collected. Univariate and multivariate survival analyses were estimated by Kaplan-Meier and Cox proportional hazards regression model, respectively. Objective response rate (ORR) and disease control rate (DCR) were assessed.Of 375 patients, 79 (21.1%) had UH: 19 (24.1%) sarcomatoid carcinoma, 15 (19.0%) mucinous adenocarcinoma, 10 (12.6%) enteric adenocarcinoma, 8 (10.1%) adenocarcinoma not otherwise specified, 7 (8.9%) large-cell neuroendocrine carcinoma, 6 (7.6%) mixed histology non-adenosquamous, 5 (6.3%) adenosquamous carcinoma, 9 (11.4%) other UH. In UH group, programmed death-ligand 1 (PD-L1)1%, 1-49%, ≥50% and unknown expression were reported in 27.8%, 22.8%, 31.7% and 17.7% patients respectively and ICI was the second/further-line in the majority of patients. After a median follow-up of 35.64 months (m), median progression-free survival (mPFS) was 2.5 m in UH [95% CI 2.2-2.9 m] versus (vs.) 2.7 m in CH [95% CI 2.3-3.2 m, P-value = .584]; median overall survival (mOS) was 8.8 m [95% CI 4.9-12.6 m] vs. 9.7 m [95% CI 8.0-11.3 m, P-value = .653]. At multivariate analyses only ECOG PS was a confirmed prognostic factor in UH. ORR and DCR were 25.3% and 40.5% in UH vs. 21.6% and 49.5% in CH [P-value = .493 and .155 respectively].No significant differences were detected between UH and CH groups. Prospective trials are needed to understand ICIs role in UH population.

Although immunotherapy has recently revolutionized standard of care in different cancer types, prostate cancer has generally failed to show dramatic responses to immune checkpoint inhibitors. As in other tumors, the goal in prostate cancer is now to target treatments more precisely on patient’s individual characteristics through precision medicine. Defects in mismatch repair, mutations in the exonuclease domain of the DNA polymerase epsilon ( POLE), high tumor mutational burden and the presence of biallelic loss of CDK12 among others, are predictive biomarkers of response to immunotherapy. In the present review, we summarize the evolving landscape of immunotherapy in prostate cancer, including precision approaches and strategies to define classes of responsive patients and scale up resistance to immune checkpoint inhibitors.

Introduction: In advanced Non-Small Cell Lung Cancer (NSCLC), Programmed Death Ligand 1 (PD-L1) remains the only used biomarker to candidate patients to immunotherapy (IO) with many limits. Given the complex dynamics of the immune system it is improbable that a single biomarker could be able to profile prediction with high accuracy. A promising solution cope with this complexity is provided by Artificial Intelligence (AI) and Machine Learning (ML), which are techniques able to analyse and interpret big multifactorial data. The present study aims at using AI tools to improve response and efficacy prediction in NSCLC patients treated with IO.MethodsReal world data (clinical data, PD-L1, histology, molecular, lab tests) and the blood microRNA signature classifier (MSC), which include 24 different microRNAs, were used. Patients were divided into responders (R), who obtained a complete or partial response or stable disease as best response, and non-responders (NR), who experienced progressive or hyperprogressive disease and those who died before the first radiologic evaluation. Moreover, we used the same data to determine if the overall survival of the patients was likely to be shorter or longer than 24 months from baseline IO. For A literature review and forward feature selection technique was used to extract a specific subset of the patients’ data. To develop the final predictive model, different ML methods have been tested, i.e., Feedforward Neural Network (FFNN), Logistic Regression (LR), K-nearest neighbours (K-NN), Support Vector Machines (SVM), and Random Forest (RF).Results 200 patients were included. 164 out of 200 (i.e., only those patients with PD-L1 data available) were considered in the model, 73 (44.5%) were R and 91 (55.5%) NR. Overall, the best model was the LR and included 5 features: 2 clinical features including the ECOG performance status and IO-line of therapy; 1 tissue feature such as PD-L1 tumour expression; and 2 blood features including the MSC test and the neutrophil-to-lymphocyte ratio (NLR). The model predicting R/NR of the patient achieves accuracy ACC= 0.756, F1 score F1=0.722, and Area Under the ROC Curve AUC=0.82. The use of the PD-L1 alone has an ACC=0.655. The accuracy of the ML models excluding some of the features from the model were as follow: without PD-L1 value (ACC=0.726), MSC (ACC=0.750), and both PD-L1 and MSC (ACC=0.707), i.e., considering only clinical features. At data cut-off (Nov 2020), median Overall Survival (mOS) for R was 38.5 months (m) (95%IC 23.9 - 53.1) vs 3.8 m (95%IC 2.8 - 4.7) for NR, with pConclusionsThe results suggest that the integration of multifactorial data provided by ML techniques is a useful tool to improve personalized selection of NSCLC patients candidates to IO. In particular, compared to PD-L1 alone the expected improvement was around 10%. In particular, the model shows that the higher the ECOG, NLR value, IO-line, and MSC test level the lower the response, and the higher PD-L1 the higher the response. Considering the difference in survival among R and NR groups, these results suggest that the model can also be used to indirectly predict survival. Moreover, a second model was able to predict long survival patients with good accuracy.

Immune-checkpoint inhibitors (ICIs) exposed the oncology community to novel immune-related adverse events (irAEs). Here, we report on a retrospective analysis of patients with melanoma who developed an ICI-related, unilateral, acute and peripheral facial nerve paralysis (Bell's palsy).We retrospectively reviewed all the cases of ICI-related Bell's palsy in patients with melanoma treated at our institution from January 2015 to January 2020. A total of five cases of ICI-related Bell's palsy were identified. Median age was 63 years. Median time-to-onset of Bell's palsy from ICIs initiation was 15 weeks. Four patients were treated with prednisone alone, whereas one patient was treated with prednisone plus valaciclovir. All the patients completely recovered from Bell's palsy without neurological sequelae. In melanoma patients treated with ICIs, Bell's palsy is a rare, neurologic irAE with a favorable outcome following administration of oral corticosteroids.

Introduction: Patients with cancer have higher risk of thrombosis compared to the general population and particularly lung adenocarcinoma is considered at high risk for venous thromboembolism. Some targetable oncogenic drivers are supposed to further increase this risk. Case description: A 35-year-old man who had developed a recurrent venous thromboembolism and pulmonary embolism (PE) was diagnosed with ROS1 rearranged non-small cell lung cancer (NSCLC). While molecular examinations were ongoing, he developed progressive respiratory failure. For PE and thrombosis worsening with detection of right heart thrombus, he underwent therapy with unfractionated heparin. Despite initial good radiologic results, only with the start of crizotinib did the patient’s clinical condition significantly improve to configure a Lazarus response. Conclusions: Cancer diagnosis should always be considered in patients with unprovoked thrombosis and, if NSCLC is diagnosed, genetic alterations should be always sought after. A possible relation between venous thromboembolism and oncogenic drivers, particularly for ALK translocations, has been hypothesized. Similarly to ALK-positive NSCLC, ROS1 rearranged disease has been associated with an increased thromboembolic risk. Further studies are needed to better evaluate this relation and to evaluate the potential benefit of a prophylactic anticoagulating treatment in this subset of patients.

Background Despite endocrine therapy being the mainstay of treatment for hormone receptor positive (HR+)/HER2− metastatic breast cancer, patients at risk of visceral crisis or doubt for endocrine sensitivity are still offered first-line chemotherapy. Maintenance hormonal therapy is generally offered at the discontinuation of chemotherapy. The MAINtenance Afinitor study is a randomised, phase III trial comparing maintenance everolimus combined with aromatase inhibitors (AIs) versus AI monotherapy in patients with disease control after first-line chemotherapy. Methods Patients with stable disease, partial response or complete response after first-line chemotherapy were randomised to everolimus plus AIs (exemestane or letrozole or anastrozole) or to AIs alone. Primary aim was progression-free survival (PFS). Secondary aims included response rate, safety and overall survival (OS). Results In total, 110 patients were randomised to everolimus + AIs (n = 52) or to AIs (n = 58). Median PFS was 11.0 months (95% confidence interval [CI] 8.1–13.8) in the everolimus + AI arm and 7.2 months (95% CI 4.7–10.9) in the AI monotherapy arm (hazard ratio [HR] 0.71, 95% CI 0.47–1.06). Objective response rate was 22.4% in everolimus + AI arm and 19.2% in AI monotherapy arm. A higher proportion of disease progression as best response was reported in the AI monotherapy arm (28.8% versus 14.3%). Median OS was 35.7 months (95% CI 26.0–47.8) in the combination arm versus 33.5 (95% CI 26.4–42.7) in the AI alone arm (HR 1.0, 95% CI 0.61–1.62). Conclusions EVE + AIs did not significantly impact on the outcome of metastatic breast cancer patients deemed suitable for first-line chemotherapy. Also taking into account treatment tolerability, maintenance endocrine therapy remains the standard. Trial registration EudraCT: 2013-004153-24.

Diarrhea is a recurrent symptom in patients with neuroendocrine tumors (NETs) and can represent different etiologies; thus, differential diagnosis is challenging. This paper distinguishes the different causes of chronic diarrhea in patients with gastroenteropancreatic NETs, with the aim to identify the most appropriate therapeutic approach. Underlying causes of diarrhea can be multifactorial, including not only diarrhea that is related to specific hormonal hypersecretory syndromes, but also diarrhea that is secondary to the following: extensive surgery which can cause pancreatic exocrine insufficiency or short bowel syndrome, treatment with somatostatin analogs or other antineoplastic agents, and bile acid malabsorption. After initial management of diarrhea with general treatments (dietary modification, use of antidiarrheals), a proper differential diagnosis is necessary to treat patients with specific etiology-driven therapeutic approaches, such as somatostatin analogs, pancreatic enzyme replacement therapy, and tryptophan hydroxylase inhibitors. In conclusion, NETs should be considered in the differential diagnosis of patients suffering from chronic diarrhea, after the exclusion of more common etiologies. Furthermore, physicians should keep in mind that several different etiologies might be responsible for diarrhea occurrence in NET patients. A prompt diagnosis of the actual cause of diarrhea is necessary to guide the treatment and a multidisciplinary approach is mandatory.

Background:Neoadjuvant anthracycline-taxane-based chemotherapy (ChT) is a standard of care treatment option for stage II–III breast cancer (BC) patients. However, the optimal duration of neoadjuvant ChT has been poorly investigated so far.Material and methods:We retrospectively retrieved clinical data of patients with stage II–III human epidermal growth factor receptor 2-negative (HER2–) BC who were treated between October 2007 and January 2018 with neoadjuvant AT (doxorubicin-paclitaxel) for three cycles followed by CMF (cyclophosphamide-methotrexate-5-fluorouracil) for three cycles (cohort A) or with four AT cycles followed by four CMF cycles (cohort B). The aim of our study was to investigate the impact of neoadjuvant ChT duration (cohort A versus cohort B) on pathological complete response (pCR) rates, disease-free survival (DFS) and overall survival (OS).Results:Of 209 HER2– BC patients included, 62 had triple-negative breast cancer (TNBC) and 147 had hormone receptor-positive (HR+) BC. Median age was 48 years (range 30–74 years). A total of 111 patients belonged to cohort A and 98 patients belonged to cohort B. pCR was detected in 29 (13.9%) patients, 25 (40.3%) of whom had TNBC and four (2.7%) had HR+ HER2– BC. Patients achieving pCR had significantly longer DFS and OS, with statistical significance reached only in patients with TNBC. We found no differences between cohort A and cohort B in terms of pCR rates (15.3% versus 12.2%; p = 0.55), DFS ( p = 0.49) or OS ( p = 0.94). The incidence of grade 3/4 adverse events was similar in cohort A versus cohort B as well (22.5% versus 19.4%; p = 0.54).Conclusion:Shorter duration of neoadjuvant anthracycline-taxane ChT was not associated with worse clinical outcomes in patients with stage II–III BC. Prospective studies are needed to evaluate whether the duration of neoadjuvant anthracycline-taxane-based ChT can be reduced in specific patient subgroups without negatively affecting clinical outcomes.

To describe the management and outcomes of loco-regionally advanced (stages III-IV) laryngeal cancer (LRALC) in elderly patients. Clinical records of 88 LRALC patients treated at our Institution from 2002 to 2017 were retrospectively reviewed. Patients were divided in 2 subgroups: age > 65 years (elderly) and age ≤ 65 years (controls). Survivals were estimated with Kaplan–Meier method and compared with log-rank test, multivariate analysis were performed with Cox proportional hazard methods. Eighty-eight LRALC patients were included: 45 elderly and 43 controls. Median follow-up was 55.3 months. Median age was 66 years (range 41–84) in the overall population, 72 years (range 66–84) in the elderly cohort. The majority (98%) of elderly patients had at least one comorbidity (ACE27 1–3), while ACE27 was 0 in 37% of controls (p = 0.0001). ECOG PS was 0 in 42% of elderly vs 79% of controls (p = 0.0029). Clinical stage (TNM eighth edition) was III in 67%, IVA in 22% and IVB in 11%. Treatment consisted in total laryngectomy (TL) in 55%, chemo-radiation in 29%, exclusive radiotherapy in 9%, and conservative surgery in 7%. In elderly patients 2-year disease-free and overall survivals were 58% and 74%, respectively. Multivariate analysis performed on the overall group of 88 patients showed that age (HR 1.07, p = 0.0006) and TNM (for both 7th and 8th Editions HR 0.27 for stage III vs IV, p = 0.0005) maintained an independent statistical significant association with OS. In this monocentric cohort, age and TNM confirmed their independent prognostic role in LRALC patients. Organ-preservation is still an unmet need in a significant portion of elderly patients.

Background: HPD has been described in 14-26% of NSCLC pts upon single agent ICI and correlates with poor survival. Currently, HPD occurrence has not been explored upon ICI-PCT and biomarkers of HPD are lacking. Although high circulating neutrophils (Ns) correlated with HPD in NSCLC pts, the role of specific Ns subsets is unknown. Methods: NSCLC pts treated with 1st line ICI as single agent or in combination with PCT were assessed for HPD and circulating Ns' phenotype. Tumor response was evaluated by RECIST 1.1. HPD required 3 assessment (2 before ICI, 1 upon ICI) and was defined as delta tumor growth rate (TGR) (TGR upon ICI - TGR before ICI) >50% and/or TGR ratio (TGR upon ICI/TGR before ICI) ≥2. Circulating low density Ns (LDNs) subtypes were assessed by flow cytometry (FC) on peripheral blood mononuclear cells (PBMCs). LDNs were defined as CD66b+CD15+ cells among CD11b+ PBMCs. Immature subtypes were defined as CD10- LDNs. Fatty acids (FA) (bodipy-palmitate) uptake was assessed by FC. T-cells of healthy donors were isolated and activated in vitro with CD3/CD28 beads in presence or not of pts' Ns to characterize their interplay. Results: Of 63 NSCLC pts, 22% had PD-L1 on tumor cells ≥50%. In the ICI single agent cohort (N=46), PD and HPD occurred in 21 (41%) and 4 (9%) pts, respectively. Before ICI start, HPD pts had significantly higher median percentage (%) of circulating immature CD10- LDNs [43.5 (min 29.5; max 82.6) vs 10.3 (min 0.1; max 79.4), p=0.01] compared to PD pts. In the ICI-PCT cohort (N=17), PD occurred in 4 (23%) pts, no HPD was reported. 5 pts had baseline CD10- LDNs ≥ 43.5% (median % of CD10- LDNs in HPD pts upon single agent ICI), 2 of them had SD and 3 PD upon ICI-PCT. In these 5 pts, CD10- LDNs significantly decreased during ICI-PCT compared to what observed in HPD pts during single agent ICI [median variation -43.4 (min -67.6, max -31.6) vs +6.9 (min -33, max +44), p= 0.03]. CD10- LDNs did not impair T-cells proliferation and IFNγ production, measured after 7 days of coculture but significantly reduced T-cell survival compared to CD10+LDNs. Baseline metabolic profile assessment showed that immature CD10- LDNs had a predominant lipid metabolism with a higher FA uptake [bodipy-palmitate mean florescence intensity (MFI) ± standard deviation (SD): 46754±11562] compared to lymphocytes [bodipy-palmitate MFI ±SD: 11542±405]. Conclusion: Higher baseline immature CD10- LDNs is a circulating biomarker of HPD upon single agent ICI. The addition of PCT prevents HPD reducing the immature Ns subset. The FA metabolism of immature LDNs does not affect T-cells proliferation/activation but reduces T-cells survival, suggesting that these two processes are differently regulated and that immature Ns reduce T-cells life span by metabolic competition. Citation Format: Roberto Ferrara, Elena Jachetti, Giuseppina Calareso, Marta Brambilla, Giuseppe Lo Russo, Claudia Proto, Arsela Prelaj, Diego Signorelli, Giulia Galli, Alessandro De Toma, Mario Occhipinti, Sara Manglaviti, Alice Labianca, Monica Ganzinelli, Sestina Maria Spanò, Giuliano Molino, Antonia Martinetti, Francesca Gabriella Greco, Marta Bini, Teresa Beninato, Filippo de Braud, Mario Paolo Colombo, Marina Chiara Garassino, Sabrina Sangaletti. Immunometabolism of circulating neutrophils in hyperprogressive disease (HPD) upon first-line PD-1/PD-L1 inhibitors (ICI) alone or in combination with platinum-based chemotherapy (PCT) in non-small cell lung cancer (NSCLC) patients (pts) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1669.

TPS4167 Background: Well-differentiated (WD) NETs are a group of rare neoplasms with limited therapeutic options. New combinations of somatostatin analogs (SSAs) and investigational drugs are warranted to improve clinical outcomes. Cabozantinib (CAB) is an orally administered inhibitor of multiple tyrosine kinases, including c-MET and Vascular Endothelial Growth Factor Receptor 2 (VEGFR2), with a pivotal role in NET pathogenesis. The biological rationale of the synergistic effects of CAB plus SSAs lies in the concomitant modulation of the RAS/MAPK and PI3K/Akt/mTOR pathways both at the level of cancer cells and tumor stroma, leading to enhanced anti-proliferative and anti-angiogenic effects. CAB exhibited encouraging activity in a recent phase II trial of patients with progressive carcinoids and pancreatic (p)NETs (Chan JA et al. JCO 2017; 35:4_suppl, 228-228). The LOLA trial is the first prospective phase II study aiming to assess the safety and activity of CAB in combination with lanreotide (LAN) in WD NETs of GEP, thoracic and of unknown origin. Clinical trial information: NCT04427787. Methods: This is a multicenter, open-label, double-cohort, non comparative, non-randomized, three-stage phase II trial. Eligible patients have to meet the following inclusion criteria: diagnosis of advanced or metastatic, progressive, non-functioning WD thoracic NETs, GEP-NETs or NETs of unknown origin with Ki67 ≥10%; positive 68Ga-PET uptake or somatostatin receptor 2 immunohistochemical (IHC) stain; maximum 1 prior systemic regimen for metastatic disease. Two cohorts will be considered: pNETs and carcinoids. In the stage I, the primary objective is to find the optimal dose of CAB in combination with LAN and to evaluate the safety of the combination (defined as the percentage of patients experiencing grade 3-5 toxicities according to NCI-CTCAE v5.0). Starting dose of CAB is 60 mg/day continuously, plus LAN 120 mg every 28 days. In stage II and III, co-primary endpoints are safety and overall response rate (ORR) according to RECIST v1.1. The useful antitumor activity to be detected is fixed in ORR > 20%. Secondary endpoints are progression-free survival and overall survival. Exploratory objectives include the assessment of IHC expression of c-MET, AXL and VEGFR2, with the aim to identify predictive or prognostic tissue biomarkers. Enrolment started in July 2020, with an expected trial duration of 42 months comprehensive of accrual, treatment and follow-up. Considering a drop out rate of 5%, the maximum number of enrolled patients will be 69. Supported by a solid rationale, the trial has the potential to generate milestone data about the synergistic effects of CAB plus LAN in a group of NET patients with relatively aggressive disease and limited therapeutic options, for whom optimal treatment sequencing is not yet defined. Clinical trial information: NCT04427787.

(1) Background. The onset of a drug–drug interaction (DDI) may affect treatment efficacy and toxicity of advanced non-small-cell lung cancer (aNSCLC) patients during epidermal growth factor receptor (EGFR) tyrosine-kinase inhibitor (TKI) use. Here we present the use of Drug-PIN® (Personalized Interactions Network) software to detect DDIs in aNSCLC patients undergoing EGFR-TKIs. (2) Methods. We enrolled patients with Stage IV aNSCLC already treated with or candidates to receive EGFR-TKIs, in any line, ECOG PS 0–2, taking at least one concomitant drug. Cancer treatments, concomitant drugs, and clinical and laboratory data were collected and inserted in Drug-PIN®. (3) Results. Ninety-two patients, median age of 68.5 years (range 43–89), were included. In total, 20 clinically relevant DDIs needing medical intervention in a total of 14 patients were identified, the 14 major DDIs were related to a high-grade interaction between TKIs and SSRIs, antipsychotics, antiepileptics, H2-receptor antagonist and calcium antagonists. A negative association between statin intake and PFS was identified (p = 0.02, HR 0.281, 95% CI 0.096–0.825). (4) Conclusions. This is the first retrospective study assessing the prevalence of DDIs, the clinical need for medical intervention and the impact of concomitant drugs on EGFR-TKIs survival in aNSCLC.

Introduction In advanced Non-Small Cell Lung Cancer (aNSCLC), Programmed Death Ligand 1 (PD-L1) remains the only used biomarker to candidate patients (pts) to immunotherapy (IO) even if its predictive accuracy is not satisfactory. Indeed, given the complex dynamics underlying the cross-talk between the tumor and its microenvironment, it is unlikely that a single biomarker could be able to profile prediction with high precision. Artificial Intelligence (AI) and machine learning (ML) are techniques able to analyze and interpret big data, which cope with this complexity. The present study aims at using AI tools to improve response and efficacy prediction in aNSCLC pts treated with IO. Methods A classification task to determine if a pt is likely to benefit from IO was formulated using complete clinical data, PD-L1, histology, molecular data, and the blood microRNA signature classifier (MSC), which include 24 different microRNAs. Pts were divided into responders (R), who obtained a partial response or stable disease as best response, and non-R, who experienced progressive disease. A forward feature selection technique based on the Akaike Information Criterion was used to extract a specific subset of the pts data, being the most informative ones for the task. To develop the final predictive model, different ML methods have been tested: K-nearest neighbors, Logistic Regression, Kernel Support Vector Machines, Feedforward Neural Network, and Random Forest. Results Of 164 enrolled pts, 73 (44.5%) were R and 91 (55.5%) non-R. At data cut-off (Nov 2020), median Overall Survival (mOS) was 10.1 (95%IC 7.0 - 13.2) months (m). mOS for R pts was 38.5 m (95%IC 23.9 - 53.1) vs 3.8 m (95%IC 2.8 - 4.7) of non-R, p Citation Format: Arsela Prelaj, Mattia Boeri, Alessandro Robuschi, Claudia Proto, Giuseppe Lo Russo, Roberto Ferrara, Giulia Galli, Alessandro De Toma, Marta Brambilla, Mario Occhipinti, Sara Manglaviti, Alice Labianca, Teresa Beninato, Marta Bini, Mavis Mensah, Monica Ganzinelli, Nicoletta Zilembo, Filippo de Braud, Gabriella Sozzi, Marcello Restelli, Alessandra Pedrocchi, Marina Chiara Garassino, Francesco Trovo. Artificial intelligence to improve selection for NSCLC patients treated with immunotherapy [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-065.

Background: Brain metastases frequently occur in patients with late-stage cancers. Treatment with high-dose glucocorticoids (GCs) is usually started to prevent or reduce tumor-related edema and its deadly complications. However, treatment with high-dose GCs is associated with serious side effects, including diabetes and immunosuppression, which could promote tumor growth or reduce the effectiveness of antitumor therapies. Based on its potential antitumor properties and on its ability to prevent GC-induced diabetes, the antidiabetic compound Metformin could reduce short-term mortality in patients with brain metastases taking high-dose GCs. Methods: The OPTIMAL study is a monocentric, open label, randomized Phase II trial in patients with brain metastases from melanoma, lung or breast cancer, who require treatment with high-dose dexamethasone, as defined as a minimum of 8 mg daily based on the clinician judgment, for at least three consecutive weeks. At enrollment, patients are randomized in a 1:1 ratio to receive high-dose dexamethasone +/- metformin 2550 mg/day for 30 days. At randomization, patients are stratified according to: tumor origin, dose of dexamethasone (8-12 vs. > 12 mg/day) and baseline fasting glycemia (< 100 vs. 100-125 mg/dl). Patients may receive concomitant radiotherapy based on the judgment of the physician. The primary study endpoint is the rate of precocious (14 days) dexamethasone-induced diabetes, as defined as fasting plasma glucose levels ≥ 126 mg/dl. Discussion: The OPTIMAL study aims to evaluate the efficacy of upfront use of metformin in preventing the onset of GCs-induced diabetes and other metabolic perturbations in patients with brain metastases from melanoma, lung or breast cancer. Other clinical objectives consist in investigating the impact of metformin on precocious mortality, deterioration of ECOG PS and local (brain) disease control rate at one month after dexamethasone initiation. The effect of dexamethasone +/- metformin on other metabolites or growth factors, including amino acids, fatty acids, ketone bodies, IGF-1, as well as on the number, activation status and metabolism of peripheral blood immune cell populations will be evaluated as well. Trial registration: The OPTIMAL trial is registered at ClinicalTrials.gov (NCT04001725, June 28, 2019) and EudraCT (2019-000105-73, January 8, 2019). Citation Format: Claudio Vernieri, Federico Nichetti, Francesca Ligorio, Emma Zattarin, Teresa Beninato, Riccardo Lobefaro, Giulia Bianchi, Giuseppe Capri, Marina Garassino, Giuseppe Lo Russo, Michele Del Vecchio, Paola Corsetto, Licia Rivoltini, Chiara Castelli, Filippo de Braud. Efficacy of metfOrmin in PrevenTIng glucocorticoid-induced diabetes in Melanoma, breAst or Lung Cancer patients with brain metastases: The phase II OPTIMAL study [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT198.