Can integrative biomarker approaches improve prediction of platinum and PARP inhibitor response in ovarian cancer?

Funingana, Ionut-Gabriel; Reinius, Marika; Petrillo, Angelica; Ang, Joo Ern; Brenton, James D.

doi:10.1016/j.semcancer.2021.02.008

Cited by 15 publications

(16 citation statements)

References 159 publications

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“…However, predicting the response for any given patient remains unresolved. This is reflected in the differences in companion diagnostics for different PARP inhibitors, ranging from clinical platinum sensitivity (agnostic of molecular tests) and BRCA1/2 mutation status to commercial HRD tests [ 73 ]. Even the cut-offs for commercial HRD tests have been shifting, highlighting the challenges in establishing a threshold for a continuous variable that informs a binary treatment decision [ 73 ].…”

Section: Molecular Subtypes Of Ovarian Carcinomasmentioning

confidence: 99%

The Evolution of Ovarian Carcinoma Subclassification

Köbel

Kang

2022

Cancers

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The phenotypically informed histotype classification remains the mainstay of ovarian carcinoma subclassification. Histotypes of ovarian epithelial neoplasms have evolved with each edition of the WHO Classification of Female Genital Tumours. The current fifth edition (2020) lists five principal histotypes: high-grade serous carcinoma (HGSC), low-grade serous carcinoma (LGSC), mucinous carcinoma (MC), endometrioid carcinoma (EC) and clear cell carcinoma (CCC). Since histotypes arise from different cells of origin, cell lineage-specific diagnostic immunohistochemical markers and histotype-specific oncogenic alterations can confirm the morphological diagnosis. A four-marker immunohistochemical panel (WT1/p53/napsin A/PR) can distinguish the five principal histotypes with high accuracy, and additional immunohistochemical markers can be used depending on the diagnostic considerations. Histotypes are further stratified into molecular subtypes and assessed with predictive biomarker tests. HGSCs have recently been subclassified based on mechanisms of chromosomal instability, mRNA expression profiles or individual candidate biomarkers. ECs are composed of the same molecular subtypes (POLE-mutated/mismatch repair-deficient/no specific molecular profile/p53-abnormal) with the same prognostic stratification as their endometrial counterparts. Although methylation analyses and gene expression and sequencing showed at least two clusters, the molecular subtypes of CCCs remain largely elusive to date. Mutational and immunohistochemical data on LGSC have suggested five molecular subtypes with prognostic differences. While our understanding of the molecular composition of ovarian carcinomas has significantly advanced and continues to evolve, the need for treatment options suitable for these alterations is becoming more obvious. Further preclinical studies using histotype-defined and molecular subtype-characterized model systems are needed to expand the therapeutic spectrum for women diagnosed with ovarian carcinomas.

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Section: Molecular Subtypes Of Ovarian Carcinomasmentioning

confidence: 99%

The Evolution of Ovarian Carcinoma Subclassification

Köbel

Kang

2022

Cancers

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“…However, different cutpoints were used to define LOH-high in these studies, which also occurred with the HRD-score analysis [114], making clinical implementation in a prospective manner challenging. Furthermore, it is important to note that the commercial HRD tests were developed in platinum-sensitive cohorts of ovarian cancer patients [122], which is in contrast to the cohorts tested in breast cancer, comprising either TNBCs or mainly gBRCA MUT populations, irrespective of prior platinum response.…”

Section: Copy Number Based "Genomic Scar" Assaysmentioning

confidence: 99%

“…A complementary approach to predict response to anti-PARP therapy is a functional assessment of the HR pathway [122,126]. Several studies have evaluated the role of RAD51, the main HRR recombinase, which is regulated by several proteins, including BRCA2, RAD52, PALB2, BRCA1, ATR, and ATM.…”

Section: Functional Biomarkers Of Hr Deficiencymentioning

confidence: 99%

Expanding the Use of PARP Inhibitors as Monotherapy and in Combination in Triple-Negative Breast Cancer

2021

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Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, and is known to be associated with a poor prognosis and limited therapeutic options. Poly (ADP-ribose) polymerase inhibitors (PARPi) are targeted therapeutics that have demonstrated efficacy as monotherapy in metastatic BRCA-mutant (BRCAMUT) TNBC patients. Improved efficacy of PARPi has been demonstrated in BRCAMUT breast cancer patients who have either received fewer lines of chemotherapy or in chemotherapy-naïve patients in the metastatic, adjuvant, and neoadjuvant settings. Moreover, recent trials in smaller cohorts have identified anti-tumor activity of PARPi in TNBC patients, regardless of BRCA-mutation status. While there have been concerns regarding the efficacy and toxicity of the use of PARPi in combination with chemotherapy, these challenges can be mitigated with careful attention to PARPi dosing strategies. To better identify a patient subpopulation that will best respond to PARPi, several genomic biomarkers of homologous recombination deficiency have been tested. However, gene expression signatures associated with PARPi response can integrate different pathways in addition to homologous recombination deficiency and can be implemented in the clinic more readily. Taken together, PARPi have great potential for use in TNBC patients beyond BRCAMUT status, both as a single-agent and in combination.

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“…Accordingly, advanced-stage, BRCA1/2wt HGSOC patients have a worse prognosis, with shorter PFS (progression free survival) than those with BRCA mutations [7]. In the era of personalized cancer therapy, validated predictive biomarkers do not exist for platinum sensitivity in women with BRCAwt ovarian cancers and predicting platinum sensitivity remains a challenge [8]. Despite various approaches have been developed, including mutational signature, transcriptomic signatures, tumor mutational burden, and functional biomarkers, no definitive results have been reached yet to guide precision treatment for women with BRCAwt ovarian cancers [8,9].…”

Section: Introductionmentioning

confidence: 99%

“…In the era of personalized cancer therapy, validated predictive biomarkers do not exist for platinum sensitivity in women with BRCAwt ovarian cancers and predicting platinum sensitivity remains a challenge [8]. Despite various approaches have been developed, including mutational signature, transcriptomic signatures, tumor mutational burden, and functional biomarkers, no definitive results have been reached yet to guide precision treatment for women with BRCAwt ovarian cancers [8,9]. Actually, the elevated level of intra-and intertumor and inter-patient heterogeneity that characterized HGSOC has been shown to be present even prior to exposure to selective pressures of therapy, this having significantly hampered biomarker discovery into actionable clinical parameters [8].…”

Section: Introductionmentioning

confidence: 99%

Identification of a novel gene signature predicting response to first-line chemotherapy in BRCA wild-type high-grade serous ovarian cancer patients

Buttarelli

Ciucci

Palluzzi

et al. 2022

J Exp Clin Cancer Res

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Background High-grade serous ovarian cancer (HGSOC) has poor survival rates due to a combination of diagnosis at advanced stage and disease recurrence as a result of chemotherapy resistance. In BRCA1 (Breast Cancer gene 1) - or BRCA2-wild type (BRCAwt) HGSOC patients, resistance and progressive disease occur earlier and more often than in mutated BRCA. Identification of biomarkers helpful in predicting response to first-line chemotherapy is a challenge to improve BRCAwt HGSOC management. Methods To identify a gene signature that can predict response to first-line chemotherapy, pre-treatment tumor biopsies from a restricted cohort of BRCAwt HGSOC patients were profiled by RNA sequencing (RNA-Seq) technology. Patients were sub-grouped according to platinum-free interval (PFI), into sensitive (PFI > 12 months) and resistant (PFI < 6 months). The gene panel identified by RNA-seq analysis was then tested by high-throughput quantitative real-time PCR (HT RT-qPCR) in a validation cohort, and statistical/bioinformatic methods were used to identify eligible markers and to explore the relevant pathway/gene network enrichments of the identified gene set. Finally, a panel of primary HGSOC cell lines was exploited to uncover cell-autonomous mechanisms of resistance. Results RNA-seq identified a 42-gene panel discriminating sensitive and resistant BRCAwt HGSOC patients and pathway analysis pointed to the immune system as a possible driver of chemotherapy response. From the extended cohort analysis of the 42 DEGs (differentially expressed genes), a statistical approach combined with the random forest classifier model generated a ten-gene signature predictive of response to first-line chemotherapy. The ten-gene signature included: CKB (Creatine kinase B), CTNNBL1 (Catenin, beta like 1), GNG11 (G protein subunit gamma 11), IGFBP7 (Insulin-like growth factor-binding protein 7), PLCG2 (Phospholipase C, gamma 2), RNF24 (Ring finger protein 24), SLC15A3 (Solute carrier family 15 member 3), TSPAN31 (Tetraspanin 31), TTI1 (TELO2 interacting protein 1) and UQCC1 (Ubiquinol-cytochrome c reductase complex assembly factor). Cytotoxicity assays, combined with gene-expression analysis in primary HGSOC cell lines, allowed to define CTNNBL1, RNF24, and TTI1 as cell-autonomous contributors to tumor resistance. Conclusions Using machine-learning techniques we have identified a gene signature that could predict response to first-line chemotherapy in BRCAwt HGSOC patients, providing a useful tool towards personalized treatment modalities.

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Can integrative biomarker approaches improve prediction of platinum and PARP inhibitor response in ovarian cancer?

Cited by 15 publications

References 159 publications

The Evolution of Ovarian Carcinoma Subclassification

The Evolution of Ovarian Carcinoma Subclassification

Expanding the Use of PARP Inhibitors as Monotherapy and in Combination in Triple-Negative Breast Cancer

Identification of a novel gene signature predicting response to first-line chemotherapy in BRCA wild-type high-grade serous ovarian cancer patients

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