Cristiano Ferlini

Cofetuzumab pelidotin (Cofe‐P) is an anti‐protein tyrosine kinase 7 (PTK7) antibody‐drug conjugate (ADC) being investigated for the treatment of adults with PTK7‐expressing, recurrent non‐small cell lung cancer (NSCLC). The first‐in‐human (FIH) trial demonstrated tolerability of dosages ≤ 2.8 mg/kg once every 3 weeks (Q3W) and ≤ 3.2 mg/kg Q2W. Population pharmacokinetics (popPK) and exposure‐response analyses were conducted to characterize Cofe‐P and unconjugated auristatin (Aur0101) payload pharmacokinetics and exposure‐efficacy (objective response rate (ORR)) and exposure‐safety (Grade ≥ 3 neutropenia, Grade ≥ 2 peripheral neuropathy or rash) endpoints to inform the selection of dosages for optimization. Data from the FIH (0.2–3.7 mg/kg Q3W, 2.1–3.2 mg/kg Q2W) and Phase 1b (2.8 mg/kg Q3W) studies were used for popPK and exposure‐response analyses. PopPK models adequately described pharmacokinetic data. Exposure‐response analyses showed that higher Cofe‐P (ADC) exposures increased the probability of achieving an objective response but also the occurrence of examined adverse events, particularly Grade ≥ 3 neutropenia. In non‐squamous epidermal growth factor receptor wild‐type NSCLC patients (≥ 90% with PTK7 2+ staining), analyses predicted that 3.2 mg/kg vs. 2.8 mg/kg Q3W dosing led to a higher ORR (35% vs. 21%) while maintaining a manageable safety profile (Grade ≥ 3 neutropenia: ≤ 39%). Predicted ORR and Grade ≥ 3 neutropenia are improvements over the standard‐of‐care, docetaxel. Dosing regimens < 2.4 mg/kg were not predicted to improve efficacy. Mean relative dose intensity was ≥ 86% across all Cofe‐P doses and schedules tested. Together, popPK and exposure‐response analyses support optimal dosing regimens of 2.4, 2.8, and 3.2 mg/kg Cofe‐P Q3W in patients with NSCLC.

The Cancer Genome Atlas (TCGA) microRNA (miRNA) initiative has revealed a pivotal role for miRNAs in cancer. Utilizing the TCGA raw data, we performed the first mapping of viral miRNA sequences within cancer and adjacent normal tissues. Results were integrated with TCGA RNA-seq to link the expression of viral miRNAs to the phenotype. Using clinical data and viral miRNA mapping results we also performed outcome analysis. Three lines of evidence lend credence to an active role of viral miRNAs in solid malignancies. First, expression of viral miRNA is consistently higher in cancerous compared to adjacent noncancerous tissues. Second, viral miRNA expression is associated with significantly worse clinical outcome among patients with early stage malignancy. These patients are also featured by increased expression of PD1/PD-L1, a pathway implicated in tumors escaping immune destruction. Finally, a particular cluster of EBV-miRNA (miR-BART2, miR-BART4, miR-BART5, miR-BART18, and miR-BART22) is associated with expression of cytokines known to inhibit host response to cancer. Quantification of specific viral miRNAs may help identify patients who are at risk of poor outcome. These patients may be candidates for novel therapeutic strategies incorporating antiviral agents and/or inhibitors of the PD-1/PD-L1 pathway.

Hypoxia selects the most aggressive and drug-resistant clones in solid malignancies. One of the pivotal transcription factors induced by hypoxia is Hif-1α. However, in serous ovarian cancer (SEOC), Hif-1α expression is not a prognostic biomarker. This study aims to assess the hypothesis that the serine-threonine kinase Nek6 functions as a downstream effector cooperating with Hif-1α in driving ovarian cancer aggressiveness. Nek6 was overexpressed and Hif-1α was silenced in A2780 cells. Nek6 was also stably silenced in Hey cells. The dependence of Nek6 expression on Hif-1α was assayed as a function of hypoxic growth conditions. Nek6 interaction with the cytoskeletal gateway of drug resistance was investigated with far western blot. The co-expression of NEK6, HIF1A, TUBB3 and GBP1 transcripts was quantified with qPCR in two cohorts of SEOC patients (346 locally treated patients and 344 from the TCGA dataset). Nek6 expression is induced by hypoxia in a Hif-1α dependent fashion. Nek6 directly interacts with GBP-1, thus being a component of the cytoskeletal gateway of drug resistance. Nek6 overexpression increases and silencing decreases the anchorage-independent growth of cultured cells. In SEOC patients, NEK6 expression is significantly correlated with HIF1A. Co-expression of NEK6, HIF1A, TUBB3 and GBP1 transcripts identifies a subset of SEOC patients characterized by poor outcome and drug resistance. This study demonstrates the functional relevance of Nek6 in the context of the adaptive response to hypoxia in SEOC. This finding may help identify a sub-population of patients at high risk of relapse to standard first-line chemotherapy.

Serous ovarian cancer (SEOC) is the deadliest gynecologic malignancy. MicroRNAs (miRNAs) are a class of small noncoding RNAs which regulate gene expression and protein translation. MiRNAs are also encoded by viruses with the intent of regulating their own genes and those of the infected cells. This is the first study assessing viral miRNAs in SEOC. MiRNAs sequencing data from 487 SEOC patients were downloaded from the TCGA website and analyzed through in-house sequencing pipeline. To cross-validate TCGA analysis, we measured the expression of miR-H25 by quantitative immunofluorescence in an additional cohort of 161 SEOC patients. Gene, miRNA expression, and cytotoxicity assay were performed on multiple ovarian cancer cell lines transfected with miR-H25 and miR-BART7. Outcome analysis was performed using multivariate Cox and Kaplan-Meier method. Viral miRNAs are more expressed in SEOC than in normal tissues. Moreover, Herpetic viral miRNAs (miR-BART7 from EBV and miR-H25 from HSV-2) are significant and predictive biomarkers of outcome in multivariate Cox analysis. MiR-BART7 correlates with resistance to first line chemotherapy and early death, whereas miR-H25 appears to impart a protective effect and long term survival. Integrated analysis of gene and viral miRNAs expression suggests that miR-BART7 induces directly cisplatin-resistance, while miR-H25 alters RNA processing and affects the expression of noxious human miRNAs such as miR-143. This is the first investigation linking viral miRNA expression to ovarian cancer outcome. Viral miRNAs can be useful to develop biomarkers for early diagnosis and as a potential therapeutic tool to reduce SEOC lethality.

Class III β-tubulin plays a prominent role in the development of drug resistance to paclitaxel by allowing the incorporation of the GBP1 GTPase into microtubules. Once in the cytoskeleton, GBP1 binds to prosurvival kinases such as PIM1 and initiates a signaling pathway that induces resistance to paclitaxel. Therefore, the inhibition of the GBP1:PIM1 interaction could potentially revert resistance to paclitaxel. A panel of 44 4-azapodophyllotoxin derivatives was screened in the NCI-60 cell panel. The result is that 31 are active and the comparative analysis demonstrated specific activity in paclitaxel-resistant cells. Using surface plasmon resonance, we were able to prove that NSC756093 is a potent in vitro inhibitor of the GBP1:PIM1 interaction and that this property is maintained in vivo in ovarian cancer cells resistant to paclitaxel. Through bioinformatics, molecular modeling, and mutagenesis studies, we identified the putative NSC756093 binding site at the interface between the helical and the LG domain of GBP1. According to our results by binding to this site, the NSC756093 compound is able to stabilize a conformation of GBP1 not suitable for binding to PIM1.

CRC cancer is one of the deadliest diseases in Western countries. In order to develop prognostic biomarkers for CRC (colorectal cancer) aggressiveness, we analyzed retrospectively 267 CRC patients via a novel, multidimensional biomarker platform. Using nanofluidic technology for qPCR analysis and quantitative fluorescent immunohistochemistry for protein analysis, we assessed 33 microRNAs, 124 mRNAs and 9 protein antigens. Analysis was conducted in each single dimension (microRNA, gene or protein) using both the multivariate Cox model and Kaplan-Meier method. Thereafter, we simplified the censored survival data into binary response data (aggressive vs. non aggressive cancer). Subsequently, we integrated the data into a diagnostic score using sliced inverse regression for sufficient dimension reduction. Accuracy was assessed using area under the receiver operating characteristic curve (AUC). Single dimension analysis led to the discovery of individual factors that were significant predictors of outcome. These included seven specific microRNAs, four genes, and one protein. When these factors were quantified individually as predictors of aggressive disease, the highest demonstrable area under the curve (AUC) was 0.68. By contrast, when all results from single dimensions were combined into integrated biomarkers, AUCs were dramatically increased with values approaching and even exceeding 0.9. Single dimension analysis generates statistically significant predictors, but their predictive strengths are suboptimal for clinical utility. A novel, multidimensional integrated approach overcomes these deficiencies. Newly derived integrated biomarkers have the potential to meaningfully guide the selection of therapeutic strategies for individual patients while elucidating molecular mechanisms driving disease progression.

Ovarian cancer is the most lethal gynecologic malignancy. Recently, NACT (Neo Adjuvant Chemotherapy) has been tested as alternative approach for the management of ovarian cancer patients. A biological predictor helpful in selecting patients for NACT would be desirable. This study was aimed at identifying actionable mechanisms of resistance to NACT.

Cancer incidence and mortality are higher in males than in females, suggesting that some gender-related factors are behind such a difference. To analyze this phenomenon the most recent Surveillance, Epidemiology and End Results (SEER) database served to access cancer survival data for the US population. Patients with gender-specific cancer and with limited information were excluded and this fact limited the sample size to 1,194,490 patients. NHANES III provided the distribution of physiologic variables in US population (n = 29,314). Cox model and Kaplan-Meier method were used to test the impact of gender on survival across age, and to calculate the gender-specific hazard ratio of dying from cancer five years following diagnosis. The distribution of the hazard ratio across age was then compared with the distribution of 65 physiological variables assessed in NHANES III. Spearman and Kolmogorov-Smirnov test assessed the homology. Cancer survival was lower in males than in females in the age range 17 to 61 years. The risk of death from cancer in males was about 30% higher than that of females of the same age. This effect was present only in sarcomas and epithelial solid tumors with distant disease and the effect was more prominent in African-Americans than Caucasians. When compared to the variables assessed in the NHANES III study, the hazard ratio almost exactly matched the distribution of free testosterone in males; none of the other analyzed variables exhibited a similar homology. Our findings suggest that male sex hormones give rise to cancer aggressiveness in patients younger than 61 years.