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Moreover, we provide preliminary evidence that reductions in the extent of phosphorylation of these biomarkers may predict responsiveness to drug therapy.
Accumulating evidence supports that MSI status may predict responsiveness to adjuvant chemotherapy.
Thus, the ability to modify muscle activation patterns after SCI may predict responsiveness to training.
The aim of this study is to identify novel phospho-proteins that may predict responsiveness to NAC treatment as there are no such biological markers available in the clinic to date.
Lynch et al (2004) and Pao et al (2004) also showed that cancer cells transfected with EGFR gene mutations showed enhanced tyrosine kinase activity in response to binding of epidermal growth factor and increased sensitivity to gefitinib and erlotinib, suggesting that specific EGFR mutations may predict responsiveness to this type of treatment.
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However, it is important to note that the exact role of measuring EGFR status in clinical setting remains unclear: EGFR expression status may not be useful as a prognostic tool (Meert et al, 2002), and may not predict responsiveness to treatment with gefitinib, a small-molecule EGFR tyrosine kinase inhibitor (Kris et al, 2003).
Our results suggest that longitudinal sampling of patients undergoing therapy may result in phospho-signatures that not only correlate with drug responsiveness but also may predict patient responsiveness to a specific class of drug.
Recent data using transoesophageal Doppler suggest that it may predict fluid responsiveness in critical care.
The mini-fluid challenge may predict fluid responsiveness with minimum risk of fluid overloading.
The level of MDM2 gene amplification (high versus low) may allow selection of patients for cancer treatment with MDM2 inhibitors and may predict their responsiveness.
In spontaneously breathing patients with hypovolemia, a IVC collapsibility >42% may predict fluid responsiveness with high specificity (97%) [26]; however, normovolemic patients with large respiratory efforts may simulate this IVC dynamics [23].
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may predict cancer
may predict mortality
may predict outcome
may restore responsiveness
may affect responsiveness
may predict risk
may predict disease
may decrease responsiveness
may regain responsiveness
may confer responsiveness
may increase responsiveness
may predict infidelity
may predict need
may facilitate responsiveness
may lack responsiveness
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