Previously, it has been shown that pancreatic ductal adenocarcinoma (PDA) tumors exhibit high levels of hypoxia, characterized by low oxygen pressure (pO2) and decreased O2 intracellular perfusion. Chronic hypoxia is strongly associated with resistance to cytotoxic chemotherapy and chemoradiation in an understudied phenomenon known as hypoxia-induced chemoresistance. The hypoxia-inducible, pro-oncogenic, serine-threonine kinase PIM1 (Proviral Integration site for Moloney murine leukemia virus 1) has emerged as a key regulator of hypoxia-induced chemoresistance in PDA and other cancers. Although its role in therapeutic resistance has been described previously, the molecular mechanism behind PIM1 overexpression in PDA is unknown. Here, we demonstrate that cis-acting AU-rich elements (ARE) present within a 38-base pair region of the PIM1 mRNA 3'-untranslated region mediate a regulatory interaction with the mRNA stability factor HuR (Hu antigen R) in the context of tumor hypoxia. Predominantly expressed in the nucleus in PDA cells, HuR translocates to the cytoplasm in response to hypoxic stress and stabilizes the PIM1 mRNA transcript, resulting in PIM1 protein overexpression. A reverse-phase protein array revealed that HuR-mediated regulation of PIM1 protects cells from hypoxic stress through phosphorylation and inactivation of the apoptotic effector BAD and activation of MEK1/2. Importantly, pharmacological inhibition of HuR by MS-444 inhibits HuR homodimerization and its cytoplasmic translocation, abrogates hypoxia-induced PIM1 overexpression and markedly enhances PDA cell sensitivity to oxaliplatin and 5-fluorouracil under physiologic low oxygen conditions. Taken together, these results support the notion that HuR has prosurvival properties in PDA cells by enabling them with growth advantages in stressful tumor microenvironment niches. Accordingly, these studies provide evidence that therapeutic disruption of HuR's regulation of PIM1 may be a key strategy in breaking an elusive chemotherapeutic resistance mechanism acquired by PDA cells that reside in hypoxic PDA microenvironments.

The integration of small kinase inhibitors and monoclonal antibodies into oncological practice has opened a new paradigm for treating cancer patients. As proteins are the direct targets of the new generations of targeted therapeutics, many of which are kinase/enzymatic inhibitors, there is an increasing interest in developing technologies capable of monitoring post-translational changes of the human proteome for the identification of new predictive, prognostic and therapeutic biomarkers. It is well known that the vast majority of the activation/deactivation of these drug targets is driven by phosphorylation. This review provides a description of the main proteomic platforms (planar and bead array, reverse phase protein microarray, phosphoflow, AQUA and mass spectrometry) that have successfully been used for measuring changes in phosphorylation level of drug targets and downstream substrates using clinical specimens. Major emphasis was given to the strengths and weaknesses of the different platforms and to the major barriers that are associated with the analysis of the phosphoproteome. Finally, a number of examples of application of the above-mentioned technologies in the clinical setting are reported.

No abstract

No abstract

Introduction: Laser Capture Microdissection (LCM) uses a laser to isolate, or capture, specific cells of interest in a complex heterogeneous tissue section, under direct microscopic visualization. Recently, there has been a surge of publications using LCM for tissue spatial molecular profiling relevant to a wide range of research topics. Areas Covered: We summarize the many advances in tissue Laser Capture Proteomics (LCP) using mass spectrometry for discovery, and protein arrays for signal pathway network mapping. This review emphasizes: a) transition of LCM phosphoproteomics from the lab to the clinic for individualized cancer therapy, and b) the emerging frontier of LCM single cell molecular analysis combining proteomics with genomic, and transcriptomic analysis. The search strategy was based on the combination of MeSH terms with expert refinement. Expert Opinion: LCM is complemented by a rich set of instruments, methodology protocols, and analytical A.I. (artificial intelligence) software for basic and translational research. Resolution is advancing to the tissue single cell level. A vision for the future evolution of LCM is presented. Emerging LCM technology is combining digital and AI guided remote imaging with automation, and telepathology, to a achieve multi-omic profiling that was not previously possible.