Papillary thyroid microcarcinoma presenting as a metastasis to the brain

The brain is a particularly rare site of metastasis from papillary microcarcinoma, with only few cases described in the literature. We present a case of 59-year-old man who presented with seizures and dysphasia due to left frontal lobe cystic mass, which was excised and turned out on histopathology to be of thyroid origin. Total thyroidectomy was performed and histology showed multifocal papillary microcarcinoma with the largest focus of 3mm with no other adverse features. The patient had ablative radioactive iodine postoperatively, with subsequent exit scan showing no uptake in the brain. Follow-up brain magnetic resonance imaging showed continuous regression of the surgical cavity. Although rare, such cases should be aggressively treated and followed up over the long term, because of reported associated high mortality.

Abstract PD04-08: Cell cycle algorithm correlates with grade of DCIS and p53 status, allows elimination of ‘intermediate grade’ disease and gives clinically meanignful information

We have previously shown that multi-parameter analysis of the DNA replication initiation machinery (Mcm2-7, geminin) and mitotic proteins (Plk1, Aurora A, H3S10ph), expressed during various phases of the cell division cycle, provides a method to accurately assess the proliferative state of dynamic tumour cell populations. We have shown that this novel form of cell cycle biomarker analysis allows separation of breast cancers into three discrete cell cycle phenotypes of major prognostic significance including (i) an out-of-cycle state, (ii) a G1-delayed/arrested state and (iii) an actively cycling state. Importantly, we identified groups of patients with apparently good grade cancers on routine clinicopathological criteria but who nevertheless exhibited the poor prognostic actively cycling phenotype (iii) and might therefore benefit from adjuvant chemotherapy. Additionally, we identified patients with typically poor prognosis tumours but which were actually cycling slowly (phenotype i or ii) and therefore likely not to have benefited from chemotherapy. Notably, when this cell cycle algorithm was used in a multi-variate analysis, the effect of Ki-67 disappeared.

We have now applied the algorithm to 72 cases of DCIS (all of which were re-graded by one pathologist for consistency) and also to a TMA of 136 cases with known outcome from the UK DICS trial. There was excellent correlation between tumour grade and p53 status. The high grade DCIS was positively associated with a high cell cycle score (actively cycling phenotype iii; 28 out of 34 tumours) and low grade DCIS was associated with a low score (namely phenotypes i and ii; 13 out of 19). Interestingly, 7 of the 10 intermediate grade DCIS could be classified as phenotype, i or iii suggesting that the algorithm may be useful in stratifying this group of patients.

A clinical correlation between phenotype III and recurrence and/or progression to invasive disease was evident. Further analysis of this from data derived from the TMAs generated from the UK DCIS trial will be presented. If the early findings are confirmed we may be able to solve the dilemma of which cases of DCIS need treatment and which we currently overtreat.

Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr PD04-08.

Targeting DNA Replication before It Starts: Cdc7 as a Therapeutic Target in p53 Mutant Her2 and Triple Negative Breast Ca

Based on protein expression profiles of core regulatory proteins involved in the G1–S and G2–M phase transitions, we have identified three distinct cell cycle phenotypes in a series of 200 breast cancers: (I) a G0 “out-of-cycle” state (18% of cases); (II) a G1 arrested/delayed state (24% cases); and (III) accelerated S-G2-M phase progression (58% of cases). The accelerated cell cycle progression phenotype had a higher risk of relapse when compared with G0 and G1-delayed/arrested phenotypes (HR=3.90 (1.81-8.4, p<0.001) and was associated with Her2 and triple negative subtypes (p<0.001). High-grade tumours with the G1 delayed/arrested phenotype showed an identical low risk of relapse compared with well-differentiated G0 tumours. In addition to its prognostic significance, the cell cycle phenotype also impacts on individualised therapeutic decisions. It is only patients showing the actively cycling, aggressive cell cycle phenotype that are likely to benefit from conventional chemotherapeutic S- or M-phase-directed agents or from the new generation of targeted cell cycle inhibitors that are now entering clinical trials.The DNA replication initiation factor Cdc7 is an emerging anti-cancer target. Cdc7 inhibition results in an abortive S phase and potent cancer cell killing. Specificity is based on normal cells undergoing a reversible G1 arrest following Cdc7 inhibition due to activation of a novel cell cycle checkpoint that is lost or impaired in cancer cells. Our analysis of the molecular circuitry underlying this replication origin activation checkpoint reveals that G1 arrest is dependent on three non-redundant checkpoint axes coordinated through the Forkhead transcription factor FoxO3a and p53. We show that only breast cancers displaying the accelerated cell cycle phenotype express elevated Cdc7 levels and are therefore highly represented in p53 mutant Her2-subtype and triple negative tumours. Breast cancers of the luminal subtype expressing low levels of Cdc7 undergo a cytostatic G1 arrest after Cdc7 inhibition due to their p53 wild type status, a checkpoint response mimicking untransformed cells. In contrast Her2 and triple negative tumours show a marked response to Cdc7 inhibitors with potent cancer-cell-specific killing as a result of (i) overexpression of the target protein and (ii) impairment of the origin activation checkpoint due to p53 lesions. Thus integrating cancer cell cycle phenotypic data with a molecular analysis of the origin activation checkpoint serves as a predictor of response to pharmacological Cdc7 inhibitors.

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 2148.

Cell cycle phase progression analysis identifies unique replication phenotypes of major prognostic and predictive significance in cancer

Abstract #5066

BACKGROUND: The cell cycle machinery acts as an integration point for information transduced through complex and redundant upstream oncogenic signalling pathways. Multiparameter analysis of core regulatory proteins involved in G1-S and G2-M cell cycle phase transitions provides a powerful biomarker readout for assessment of the cell cycle state. We have applied this novel algorithm to breast cancer, investigating its cell cycle kinetics, and determining how this impacts on pathobiology and disease progression in-vivo.
 METHODS AND FINDINGS: Protein expression profiles of key constituents of the DNA replication licensing pathway (Mcm2, geminin) and mitotic machinery (Plk1, Aurora A, Aurora substrate Histone H3S10ph), mediators of G1-S and G2-M transition respectively, were generated for a cohort of 182 patients. Arrested differentiation and development of genomic instability was associated with increased engagement of cells into the cell division cycle (p<0.0001). Three unique cell cycle phenotypes were identified; (I) well differentiated tumours composed predominantly of Mcm2 negative cells indicative of an out-of-cycle state (18% of cases), (II) high Mcm2 expressing tumours but with low geminin, Aurora A, Plk1 and H3S10ph levels (S-G2-M progression markers) indicative of a G1 delayed/arrested state (24% cases), (III) high expressing Mcm2 tumours, but also expressing high levels of the S-G2-M progression markers, indicative of accelerated cell cycle progression (58% of cases). The accelerated cell cycle phenotype had a significantly higher risk of relapse when compared with out-of-cycle and G1 delayed/arrested tumour phenotypes (HR=3.90 [1.81-8.40], p<0.001). Notably high grade tumours with the G1 delayed/arrested phenotype showed an identical low risk of relapse to well differentiated out-of-cycle tumours (HR=1.00 [0.22-4.46], p=0.99), suggesting that many patients are receiving inappropriate S-G2-M phase directed adjuvant chemotherapy.
 CONCLUSIONS: This biomarker algorithm provides novel insights into the cell cycle state of dynamic tumour cell populations in-vivo, information that impacts on individualised therapeutic decisions. The cell cycle phenotype has a major influence on disease progression, identifying those patients at most risk of relapse. Importantly, it is only patients displaying an accelerated phenotype, tumours that show S-G2-M phase transit, that are likely to derive benefit from S and G2-M phase specific adjuvant chemotherapeutic agents and mechanistic drugs.

Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 5066.