DNA damage response and repair genes in advanced bone and soft tissue sarcomas: An 8-gene signature as a candidate predictive biomarker of response to trabectedin and olaparib combination

Alessandra Merlini, Maria Laura Centomo, Giulio Ferrero, Giulia Chiabotto, Umberto Miglio, Enrico Berrino, Giorgia Giordano, Silvia Brusco, Alberto Pisacane, Elena Maldi, Ivana Sarotto, Federica Capozzi, Cristina Lano, Claudio Isella, Giovanni Crisafulli, Massimo Aglietta, Angelo Paolo Dei Tos, Marta Sbaraglia, Dario Sangiolo, Lorenzo D'Ambrosio, Alberto Bardelli, Ymera Pignochino, Giovanni Grignani, Alessandra Merlini, Maria Laura Centomo, Giulio Ferrero, Giulia Chiabotto, Umberto Miglio, Enrico Berrino, Giorgia Giordano, Silvia Brusco, Alberto Pisacane, Elena Maldi, Ivana Sarotto, Federica Capozzi, Cristina Lano, Claudio Isella, Giovanni Crisafulli, Massimo Aglietta, Angelo Paolo Dei Tos, Marta Sbaraglia, Dario Sangiolo, Lorenzo D'Ambrosio, Alberto Bardelli, Ymera Pignochino, Giovanni Grignani

Abstract

Background: Advanced and unresectable bone and soft tissue sarcomas (BSTS) still represent an unmet medical need. We demonstrated that the alkylating agent trabectedin and the PARP1-inhibitor olaparib display antitumor activity in BSTS preclinical models. Moreover, in a phase Ib clinical trial (NCT02398058), feasibility, tolerability and encouraging results have been observed and the treatment combination is currently under study in a phase II trial (NCT03838744).

Methods: Differential expression of genes involved in DNA Damage Response and Repair was evaluated by Nanostring® technology, extracting RNA from pre-treatment tumor samples of 16 responder (≥6-month progression free survival) and 16 non-responder patients. Data validation was performed by quantitative real-time PCR, RNA in situ hybridization, and immunohistochemistry. The correlation between the identified candidate genes and both progression-free survival and overall survival was investigated in the publicly available dataset "Sarcoma (TCGA, The Cancer Genome Atlas)".

Results: Differential RNA expression analysis revealed an 8-gene signature (CDKN2A, PIK3R1, SLFN11, ATM, APEX2, BLM, XRCC2, MAD2L2) defining patients with better outcome upon trabectedin+olaparib treatment. In responder vs. non-responder patients, a significant differential expression of these genes was further confirmed by RNA in situ hybridization and by qRT-PCR and immunohistochemistry in selected experiments. Correlation between survival outcomes and genetic alterations in the identified genes was shown in the TCGA sarcoma dataset.

Conclusions: This work identified an 8-gene expression signature to improve prediction of response to trabectedin+olaparib combination in BSTS. The predictive role of these potential biomarkers warrants further investigation.

Keywords: DNA damage response and repair genes; bone and soft tissue sarcomas; olaparib; predictive biomarkers; trabectedin.

Conflict of interest statement

GGr has received fees for consulting/advisory roles from PharmaMar, Lilly, Novartis, Bayer, and Eisai. LDA received travel grant from PharmaMar and Lilly. MA has received fees for consulting/advisory roles from Bristol- Myers Squibb, Merck, and Roche. AB served in a consulting/advisory role for Illumina and Inivata. AB is cofounder and shareholder of NeoPhore. AB is a member of the NeoPhore scientific advisory board. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2022 Merlini, Centomo, Ferrero, Chiabotto, Miglio, Berrino, Giordano, Brusco, Pisacane, Maldi, Sarotto, Capozzi, Lano, Isella, Crisafulli, Aglietta, Dei Tos, Sbaraglia, Sangiolo, D’Ambrosio, Bardelli, Pignochino and Grignani.

Figures

Figure 1
Figure 1
(A) Volcano plot showing differential expression of DDRR genes in responder vs. non-responder patients. (B) Boxplot showing differential expression of DDRR genes in responder vs. non-responder patients, with normalized expression. P-value by Wilcoxon Rank-Sum test. *p<0.05; **p<0.01.
Figure 2
Figure 2
RNA ISH of selected genes in responder vs. non-responder patients. (A) Higher expressed genes in responder patients (B) higher expressed genes in non-responders (C). Heatmap showing differential RNA ISH staining between responder and non-responder patients. ISH score was assigned by an expert pathologist on the basis of staining intensity and percentage of positive cells. P-value was calculated by Chi-square test. *p<0.05; **p<0.01.
Figure 3
Figure 3
Validation Assays (A) Expression levels of representative genes (CDKN2A, left; and APEX2, right) among responder and non-responder patients. Statistically significant differential expression was shown between the two groups (Wilcoxon rank-sum test). (B) Representative IHC staining of CDKN2A/p16 in tumor samples from responder and non-responder patients. (C) Box plot distribution of CDKN2a/p16 expression level (percentage of IHC positive cells) in responders and non-responders patients.
Figure 4
Figure 4
Oncoprint and heatmap of candidate biomarkers in the TCGA sarcoma cohort.
Figure 5
Figure 5
Kaplan-Meier curves showing Overall Sirvival in the sarcoma TCGA cohort, according to selected candidate biomarker genes (BLM, A, and MAD2L2, B).

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