The sexist behaviour of immune checkpoint inhibitors in cancer therapy? The sexist behaviour of immune checkpoint inhibitors in cancer therapy?

Background: About 10% of NSCLCs are mutated in KRAS and impaired in STK11/LKB1, a genetic background associated with poor prognosis, caused by an increase in metastatic burden and resistance to standard therapy. LKB1 is a protein involved in a number of biological processes and is particularly important for its role in the regulation of cell metabolism. LKB1 alterations lead to protein loss that causes mitochondria and metabolic dysfunction that makes cells unable to respond to metabolic stress. Different studies have shown how it is possible to interfere with cancer metabolism using metformin and caloric restriction (CR) and both modify the tumor microenvironment (TME), stimulating the switch from “cold” to “hot”. Given the poor therapeutic response of KRAS^mut/LKB1^mut patients, and the role of LKB1 in cell metabolism, we examined whether the addition of metformin and CR enhanced the response to chemo or chemo-immunotherapy in LKB1 impaired tumors. Methods: Mouse cell lines were derived from lung nodules of transgenic mice carrying KRAS^G12D with either functional LKB1 (KRAS^G12D/LKB1^wt) or mutated LKB1 (KRAS^G12D/LKB1^mut). Once stabilized in vitro, these cell lines were inoculated subcutaneously and intramuscularly into immunocompetent mice. Additionally, a patient-derived xenograft (PDX) model was established by directly implanting tumor fragments from patient into immunocompromised mice. The mice bearing these tumor models were subjected to treatment with chemotherapy or chemo-immunotherapy, both as standalone regimens and in combination with metformin and CR. Results: Our preclinical results indicate that in NSCLC KRAS^mut/LKB1^mut tumors, metformin and CR do enhance the response to chemo and chemo-immunotherapy, inducing a metabolic stress condition that these tumors are not able to overcome. Analysis of immune infiltrating cells did not bring to light any strong correlation between the TME immune-modulation and the tumor response to metformin and CR. Conclusion: Our in vitro and in vivo preliminary studies confirm our hypothesis that the addition of metformin and CR is able to improve the antitumor activity of chemo and chemoimmunotherapy in LKB1 impaired tumors, exploiting their inability to overcome metabolic stress.

(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.

(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.

Background: The optimal anti-angiogenic strategy as second-line treatment in RAS wild-type metastatic colorectal cancer (mCRC) treated with anti-EGFR (Epidermal Growth Factor Receptor) based first-line treatment is still debated. Methods: This multicenter, real-world, retrospective study is aimed at evaluating the effectiveness of second-line Bevacizumab- and Aflibercept-based treatments after an anti-EGFR based first-line regimen. Clinical outcomes measured were: objective response rate (ORR), progression free survival (PFS), overall survival (OS) and adverse events (AEs) profiles. Results: From February 2011 to October 2019, 277 consecutive mCRC patients received Bevacizumab-based (228, 82.3%) or Aflibercept-based (49, 17.7%) regimen. No significant difference was found regarding ORR. The median follow-up was 27.7 months (95%CI: 24.7–34.4). Aflibercept-treated group had a significantly shorter PFS compared to Bevacizumab-treated group (5.6 vs. 7.1 months, respectively) (HR = 1.34 (95%CI: 0.95–1.89); p = 0.0932). The median OS of the Bevacizumab-treated group and Aflibercept-treated group was 16.2 (95%CI: 15.3–18.1) and 12.7 (95%CI: 8.8–17.5) months, respectively (HR= 1.31 (95%CI: 0.89–1.93) p = 0.16). After adjusting for the key covariates (age, gender, performance status, number of metastatic sites and primary tumor side) Bevacizumab-based regimens revealed to be significantly related with a prolonged PFS (HR = 1.44 (95%CI: 1.02–2.03); p = 0.0399) compared to Aflibercept-based regimens, but not with a prolonged OS (HR = 1.47 (95%CI: 0.99–2.17); p = 0.0503). The incidence of G3/G4 VEGF inhibitors class-specific AEs was 7.5% and 26.5% in the Bevacizumab-treated group and the Aflibercept-treated group, respectively (p = 0.0001). Conclusion: Our analysis seems to reveal that Bevacizumab-based regimens have a slightly better PFS and class-specific AEs profile compared to Aflibercept-based regimen as second-line treatment of RAS wild-type mCRC patients previously treated with anti-EGFR based treatments. These results have to be taken with caution and no conclusive considerations are allowed.