Abstract 1534: Amplification of PITPNC1 affects breast cancer progression
Bibliographic record
Abstract
Abstract Introduction Identification of driver mutations at single gene level and determination of their respective contribution to the enhanced invasive potential of cancer cells, via expression profiling and functional assays, are indispensable steps toward elucidating breast cancer pathobiology. In our previous array comparative genomic hybridization studies, gain in a region of chromosome 17, 17q23.3-24.3, was frequently observed in invasive duct carcinoma (IDC) patients with lymph node metastasis. Particularly, phosphatidylinositol transfer protein, cytoplasmic 1 (PITPNC1), found in 17q24.2, was associated with higher histological grade, larger tumor size, positive HER2 staining, and poorer prognosis from the analysis of a NKI dataset. PITPNC1 is involved in signal transduction and intracellular lipid transport, and may be an essential part of the epidermal growth factor signaling pathway. Additionally, amplification of PITPNC1 via the loss of microRNA-126 suppression has been implicated in metastatic angiogenesis and colonization. In this study, we aim to assess the role of PITPNC1 in the development of aggressive breast cancer by evaluating its effects on breast cancer progression and invasion. Method A total of 21 samples - 13 pure duct carcinoma in situ (DCIS), 8 IDC with or without lymph node metastasis - were used for the preliminary round of this study. Formalin-fixed and paraffin-embedded tissue blocks were microdissected and whole genome amplified using ligation-mediated PCR. Amplified DNA was subjected to quantitative real-time PCR. Copy number alterations of PITPNC1 were calculated with Livak method, using B2M as the reference gene. Lipofectamine transfection overexpressing PITPNC1 in non-invasive MCF-10A and invasive MCF7, MD-MB-231 cell lines was prepared for subsequent in vitro assays. Proliferation and migration capabilities associated with PITPNC1 overexpression is being evaluated using MTT assay and transwell migration assay. Result From preliminary qPCR data, PITPNC1 was shown to be amplified in DCIS samples (p = 0.0025) and IDC samples (p = 0.0093). The 95% confidence intervals of fold difference against normal breast tissue control are [7.1, 23.4] and [5.7, 24.4] respectively. PITPNC1 overexpressing MCF-10A cells exhibit a higher proliferation rate in culture compared to controls. Conclusion Consistent amplification of PITPNC1 is seen in both DCIS and IDC cases. However, it is still unclear if PITPNC1 amplification is a result of a single mutational event occurring early in cancer progression or a cumulative effect occurring over time. Additional qPCR on paired samples against a pooled control would be necessary to determine its contribution to invasion. The regularity of copy number gain in the PITPNC1 locus and its association with HER2 expression highlight its predictive potential as a novel biomarker for tumorigenesis or invasion. Citation Format: Peiqi Wang, Ranju Nair, Nisha Kanwar, Grace Cheung, Susan J. Done. Amplification of PITPNC1 affects breast cancer progression. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1534.
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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) | 0.004 | 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".