RICTOR/PI3K/mTOR as a clinically relevant driver of poor prognosis in squamous cell lung carcinoma (SqCLC): Preliminary results of prognostic outliers according to a validated clinicopathological model

Date

08 Oct 2016

Session

Poster Display

Presenters

Sara Pilotto

Citation

Annals of Oncology (2016) 27 (6): 407-410. 10.1093/annonc/mdw381

Authors

S. Pilotto¹, M. Simbolo², I. Sperduti³, S. Novello⁴, C. Vicentini², U. Peretti¹, S. Pedron², M. Milella⁵, A. Mafficini², P. Visca⁶, M. Volante⁷, F. Facciolo⁸, A. Santo⁹, M. Infante¹⁰, L. Carbognin¹, M. Brunelli², M. Chilosi², A. Scarpa², G. Tortora¹, E. Bria¹

Author affiliations

¹ Medical Oncology, AOU Integrata Verona "Borgo Roma", 37134 - Verona/IT
² Pathology And Diagnostics, Azienda Ospedaliera Universitaria Integrata Verona-"Borgo Roma", 37134 - Verona/IT
³ Biostatistic Unit, Istituto Regina Elena, 00144 - Roma/IT
⁴ Department Of Oncology, University of Turin, Orbassano/IT
⁵ S. C. Oncologia Medica A, Istituto Regina Elena, 00144 - Roma/IT
⁶ Anatomia Patologica, Istituto Regina Elena, 00144 - Roma/IT
⁷ Department Of Oncology, University of Turin, 00000 - Orbassano/IT
⁸ Thoracic Surgery, Istituto Regina Elena, 00144 - Roma/IT
⁹ Medical Oncology, Azienda Ospedaliera Universitaria Integrata Verona-"Borgo Roma", 37134 - Verona/IT
¹⁰ Chirurgia Toracica, AOU Integrata Verona, 37138 - Verona/IT

Resources

Abstract 3735

Background

We previously validated a clinical risk classification model for resected SqCLC by combining clinicopathological predictors to discriminate patients' (pts) prognosis (Pilotto JTO 2015). Here we investigate the molecular portrait of prognostic outliers to identify differentially expressed, potentially druggable molecular targets (AIRCMFAG project no. 14282).

Methods

On the basis of the published 3-class model, 176 and 46 pts with good and poor prognosis, respectively, were identified. Next Generation Sequencing (NGS) analysis (Ion Proton system, Ion Ampliseq custom panel) evaluating Somatic Mutations (SM) and Copy Number Alternations (CNA) of 44 genes was performed; RNA expression, immunohistochemistry (IHC), immunofluorescence (FISH) were performed on Tissue Micro-Arrays (TMA). Descriptive statistics was adopted; continuous variables were dichotomized according to AUC or medians.

Results

The distribution of relevant SM and CNA analysis of 60 pts according to prognosis (good: 27; poor: 33) is reported in the table.

Analysis (NGS)	Gene	Good: 27 pts [%]	Poor: 33 pts [%]	p-value
SM	PI3KCA	0	3 [9.1]	0.24
	NOTCH1	2 [7.4]	0	0.19
	CUL3	2 [7.4]	0	0.19
	DDR2	3 [11.1]	0	0.085
	CDH10	4 [14.8]	1 [3.0]	0.16
	CDH1	3 [11.1]	1 [3.0]	0.3
CNA Gains	RICTOR	1 [3.7]	9 [27.3]	0.017
	SOX2	20 [74.1]	17 [51.5]	0.11
CNA Losses	CDKN2A	6 [22.2]	1 [3.0]	0.038
	PTEN	11 [40.7]	17 [51.5]	0.57
	RB1	8 [29.6]	17 [51.5]	0.12
	SMAD4	9 [33.3]	19 [57.6]	0.074

No significant differences in terms of phospho-mTOR and PD-L1 IHC expression were found in the 2 different prognostic subgroups. Patients with concurrent high PD1, SNAI, and Vimentin RNA expression were significantly more likely to be at poor prognosis (p = 0.003).

Conclusions

Although performed on a limited number of pts, the approach to comprehensively analyze DNA, RNA and proteins, using different methodologies, strengthens the clinically relevance of RICTOR/PI3K/mTOR signaling cascade activation in determining the poor prognosis of SqCLC. The possibility to inhibit this pathway with selective agents is currently under investigation in in vitro preclinical models.

Clinical trial identification

Legal entity responsible for the study

University of Verona, Verona, Italy

Funding

Associazione Italiana per la Ricerca sul Cancro (AIRC): MFAG Project 14282.

Disclosure

All authors have declared no conflicts of interest.

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