Abstract 322: Distinct pools of ShcA coupled tyrosine kinase signaling influences breast tumor heterogeneity and therapeutic responsiveness
Bibliographic record
Abstract
Abstract Phospho-tyrosine (pTyr) signaling networks are frequently activated in breast cancers (BrCa) and are considered to be major oncogenic drivers of tumor progression. Therapeutic interventions, such as the tyrosine kinase (TK) inhibitor Trastuzumab, focus on targeting TK activity and downstream effectors. Although successful for early stage tumors, a subset of patients experience relapse due to intrinsic or acquired resistance. This includes activation of alternative receptor tyrosine kinase (RTK) and/or cytoplasmic TKs, many of which require recruitment of the adaptor protein, ShcA. ShcA is a key convergence point downstream of RTKs and serves to integrate multiple signal transduction pathways dysregulated in BrCa. Specifically, ShcA contains two pTyr binding motifs including an amino-terminal PTB domain and a carboxy-terminal SH2 domain which facilitate its interactions with TKs including ErbB2 and Src Family Kinases (SFK), respectively. The CH-1 domain houses three tyrosine phosphorylation sites at residues 239/240 and 317 which transduce Ras-dependent and independent signals. Using a well characterized transgenic mouse model of BrCa where ShcA can no longer engage the transforming oncogene through its PTB domain, we demonstrate that loss of PTB-driven ShcA (ShcA-PTBMut) signaling delays mammary tumor onset. However, once formed, the growth and angiogenic potential of these tumors is significantly increased relative to control mice. Increased growth potential of ShcA-PTBMut tumors is associated with the hyper-activation of the c-Src tyrosine kinase. Deletion of c-Src in ShcA-PTBMut breast tumor cells significantly delays tumor onset but is dispensable for the growth of tumors that retain an intact ShcA PTB domain. These data suggest that the ShcA PTB domain can recruit negative regulators that limit the activation of downstream tumorigenic signaling networks. Interestingly, tumors expressing ShcA-PTBMut debilitated in SH2 driven pTyr interactions (SH2Mut), are significantly delayed in tumor onset relative to ShcA-PTBMut controls. Paradoxically, deletion of c-Src in the context of ShcA-PTBMut-SH2Mut further accelerates tumor growth which is attributed to increased levels of Fyn and Lyn. These observations support the high dependence of intracellular ShcA pools on other SFK family members to retain tumorigenic potential when adapting to low levels and/or activity of c-Src. We demonstrate that uncoupling of PTB-driven ShcA signaling from upstream RTKs can potentiate ShcA signaling from intracellular pools to hyper-activate SFKs. This data is clinically relevant as c-Src is frequently hyper-activated in Trastuzumab-resistant BrCa. This is the first study to identify a tumor suppressive role of the ShcA PTB domain and to characterize an intrinsic ShcA SH2 domain-SFK dependent resistance mechanism downstream of activated RTKs in mammary tumorigenesis. Citation Format: Jacqueline R. Ha, Ryuhjin Ahn, Young Kyuen Im, Valerie Sabourin, Harvey W. Smith, Ivan Topisirovic, Tony Pawson, Peter Siegel, William J. Muller, Josie Ursini-Siegel. Distinct pools of ShcA coupled tyrosine kinase signaling influences breast tumor heterogeneity and therapeutic responsiveness [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 322. doi:10.1158/1538-7445.AM2017-322
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".